Comments Concerning the National Swedish Contaminant Monitoring Programme in Marine Biota, 2011

Sakrapport

Övervakning av metaller och organiskamiljögifter i marin biota, 2009

Överenskommelse 212 0818, dnr 235-3405-08Mm

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SWEDISH · MUSEUM · OF · NATURAL · HISTORY

The Department of Contaminant Research

P.O. Box 50007

SE-104 05 Stockholm

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Comments Concerning the NationalSwedish Contaminant MonitoringProgramme in Marine Biota, 20092009-08-14

Anders Bignert, Sara Danielsson, Elisabeth NybergThe Department of Contaminant Research, Swedish Museum of Natural History

Lillemor Asplund, Ulla Eriksson and Urs BergerDepartment of Applied Environmental Science, Stockholm University

Peter HaglundDepartment of Chemistry, Umeå University

Chemical analysis:

Organochlorines and perflourinated substancesDepartment of Applied Environmental Science, Stockholm University

Trace metalsDepartment of Environmental Assessment, Swedish University of AgriculturalSciences

PCDD/PCDFDepartment of Chemistry, Umeå University

PAHsIVL Swedish Environmental Research Institute

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Contents

1 Introduction .................................................................................. 4

2 Summary 2007/08 ......................................................................... 6

3 Sampling ....................................................................................... 8

4 Sample matrices......................................................................... 11

5 Sampling sites ............................................................................ 17

6 Analytical methods..................................................................... 25

7 Statistical treatment, graphical presentation ........................... 30

8 The power of the programme .................................................... 34

9 Condition..................................................................................... 39

10 Fat content................................................................................ 42

11 Mercury..................................................................................... 48

12 Lead .......................................................................................... 57

13 Cadmium .................................................................................. 64

14 Nickel ........................................................................................ 72

15 Chromium................................................................................. 76

16 Copper ...................................................................................... 79

17 Zinc ........................................................................................... 84

18 PCB's, Polychlorinated biphenyles........................................ 89

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19 DDT's, Dichlorodiphenylethanes ......................................... 100

20 HCH’s, Hexachlorocyclohexanes......................................... 107

21 HCB, Hexachlorobenzene..................................................... 117

22 PCDD/PCDF, Polychlorinated Dioxins and Dibenzofurans. 124

23 Polybrominated flame retardants ......................................... 128

24 PAHs, Polyaromatic Hydrocarbons ...................................... 135

25 PFCs, Perfluorinated compounds......................................... 145

26 References.............................................................................. 150

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1 IntroductionThis report gives a summary of the monitoring activities within the national Swedishcontaminant programme in marine biota. It is the result from the joint efforts of: theDepartment of Applied Environmental Science at Stockholm University (analyses oforganochlorines), the Department of Environmental Assessment at Swedish University ofAgricultural Sciences (analyses of heavy metals), Department of Chemistry at UmeåUniversity (analyses of PCDD/PCDF) and the Department of Contaminant Research at theSwedish Museum of Natural History (co-ordination, sample collection administration,sample preparation, recording of biological variables, storage of frozen biological tissues inthe Environmental Specimen Bank for retrospective studies, data preparation and statisticalevaluation). The monitoring programme is financiated by the Environmental ProtectionAgency (EPA) in Sweden.

The data of concern in this report represent the bioavailable part of the investigatedcontaminants i.e. the part that has virtually passed through the biological membranes andmay cause toxic effects. The objectives of the monitoring program in marine biota could besummarised as follows:

to estimate the levels and the normal variation of various contaminants in marine biotafrom several representative sites, uninfluenced by local sources, along the Swedish coasts.The goal is to describe the general contaminant load and to supply reference values forregional and local monitoring programmes

to monitor long term time trends and to estimate the rate of found changes.quantified objective: to detect an annual change of 10% within a time period of 10 years with a power of 80%at a significance level of 5%.

to estimate the response in marine biota of measures taken to reduce the discharges ofvarious contaminantsquantified objective: to detect a 50% decrease within a time period of 10 years with a power of 80% at asignificance level of 5%.

to detect incidents of regional influence or widespread incidents of ‘Chernobyl’-character and to act as watchdog monitoring to detect renewed usage of bannedcontaminants.quantified objective: to detect an increase of 200% a single year with a power of 80% at a significance level of5%.

to indicate large scale spatial differencesquantified objective: to detect differences of a factor 2 between sites with a power of 80% at a significancelevel of 5%.

to explore the development and regional differences of the composition and pattern ofe.g. PCB’s, HCH’s, DDT’s, PCDD/F, PBDE/HBCD, PAH’s and PFC’s as well as the ratiosbetween various contaminants.

the time series are also relevant for human consumption since important commercial fishspecies like herring and cod are sampled. A co-operation with the Swedish FoodAdministration is established. Sampling is also co-ordinated with SSI (Swedish RadiationProtection Authority) for analysing radionuclides in fish and blue mussels (HELCOM,1992).

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all analysed, and a large number of additional specimens, of the annually systematicallycollected material are stored frozen in the Environmental Specimen Bank. This invaluablematerial enables future retrospective studies of contaminants impossible to analyse today aswell as control analyses of suspected analytical errors.

although the programme is focused on contaminant concentration in biota, also thedevelopment of biological variables like e.g. condition factor (CF), liver somatic index(LSI) and fat content are monitored at all sites. At a few sites, integrated monitoring withfish physiology and population are running in co-operation with the University ofGothenburg and the Swedish Board of Fisheries.

experiences from the national programme with several time series of over 30 years can beused in the design of regional and local monitoring programmes.

the perfectly unique material of high quality and long time series is further used toexplore relationships among biological variables and contaminant concentrations in varioustissues; the effects of changes in sampling strategy, the estimates of variance componentsand the influence on the concept of power etc.

the accessibility of high quality data collected and analysed in a consistent manner is anindispensable prerequisite to evaluate the validity of hypothesis and models concerning thefate and distribution of various contaminants. It could furthermore be used as input of ‘real’data in the ongoing model building activities concerning marine ecosystems in general andin the Baltic and North Sea environment in particular.

the contaminant programme in marine biota constitute an integrated part of the nationalmonitoring activities in the marine environment as well as of the international programmeswithin ICES, OSPARCOM, HELCOM and EU.

The present report displays the timeseries of analysed contaminants in biota andsummarises the results from the statistical treatment. It does not in general give thebackground or explanations to significant changes found in the timeseries. Increasingconcentrations thus, urge for intensified studies.

Short comments are given for temporal trends as well as for spatial variation and, for somecontaminants, differences in geometric mean concentration between various species caughtat the same site. Sometimes notes of seasonal variation and differences in concentrationbetween tissues in the same species are given. This information could say something aboutthe relative appropriateness of the sampled matrix and be of help in designing monitoringprogrammes. In the temporal trend part, an extract of the relevant findings is summarised inthe 'conclusion'-paragraph. It should be stressed though, that geographical differences maynot reflect antropogenic influence but may be due to factors like productivity, temperature,salinity etc.

The report is continuously updated. The date of the latest update is reported at the beginningof each chapter. The creation date of each figure is written in the lower left corner.

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2 Summary 2007/08A short summary of the results up to year 2007/08 is given below. Graphical presentations,tables and details are given in the following chapters.

The condition of herring in the Baltic is decreasing, together with the fat content inherring muscle, in all autumn and spring time series except at Ängskärsklubb (autumnand spring). During recent years this decrease has stopped at Landsort and Utlängan andthe condition and fat content have improved somewhat.

Due to a change of method for metal analysis in 2004, values after 2003 are notpresented, since the values are uncertain. A change of analytical laboratory for metalanalysis will occur under 2009.

Lead concentrations in herring, cod and perch livers are decreasing in almost all timeseries, both on the Swedish west coast and in the Baltic.

The increasing trends of cadmium concentrations in herring liver from the Baltic Properand from the Bothnian Sea reported for the period 1980 to 1997 seems to have turnedinto a decreasing trend during recent years. The levels are however not lower than in thebeginning of the 1980-ies.

Cadmium concentrations in blue mussels from the Baltic Proper are about 5 timeshigher than the suggested background levels for the North Sea and 3 times higher thanin blue mussels from the Swedish west coast.

CB-153 is decreasing in herring, cod, perch and guillemot from the Baltic Proper andalso in herring and blue mussel from Fladen at the Swedish west coast.

CB-153 shows significantly higher concentrations in herring (generally more than threetimes) from the Baltic Proper and the Bothnian Sea compared to the Swedish westcoast.

HCH’s are decreasing at almost all sites with time series long enough to permit astatistical trend analysis.

HCB is decreasing in herring, cod, perch and guillemot from the Baltic Proper and alsoin herring and cod from Fladen at the Swedish west coast.

There was a significant decrease of TCDD/TCDF in guillemot eggs from St Karlsöbetween 1970 and the middle of the 80-ies, after which the decrease has levelled out. Inherring there is no decrease in TCDD-equivalents during the investigated time period1990-2007. At Harufjärden there has even been a significant increase in lipid weightconcentrations.

TCDD/TCDF shows clearly higher concentrations in herring from the Baltic Proper, theBothnian Sea and the Bothnian Bay compared to the Swedish west coast.

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HBCD is increasing in guillemot eggs from the Baltic Proper.

PFOS in guillemot eggs from the Baltic Proper show an increasing trend of 10 % peryear until the end of the 1990s. The recent development of the trend is uncertain due tolarge inter-annual variations.

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3 Sampling

3.1 Sampling area

The sampling area is generally defined by a central co-ordinate surrounded by a circle of 3nautical miles. The exact sampling location should be registered at collection. Generaldemands on sampling sites within the national contaminant monitoring programme aredefined in chap. 5.

3.2 Collected specimens

For many species adult specimens are less stationary than sub-adults and represent a morerecent picture of the contaminant load since many contaminants accumulates over time. Toincrease comparability between years, young specimens are generally collected. However,the size of the individual specimens has to be big enough to allow individual chemicalanalysis. Thus the size and age of the specimens vary between species and sites (see chap.4). To avoid possible contribution of between-year variance due to sex differences the samesex (females) is analysed each year in most timeseries. In the past both sexes were used andthus, at least for the oldest time series, both sexes appear. To achieve the requested numberof individual specimens of the prescribed age range and sex, about 50 - 100 specimens arecollected at each site.

Only healthy looking specimens with undamaged skin are selected.

The collected specimens are placed individually in polyethene plastic bags, deep frozen assoon as possible and transported to the sample preparation laboratory.

Collected specimens, not used for the annual contaminant monitoring programme are storedin the Environmental Specimen Bank (see Odsjö 1993 for further information). Thesespecimens are thoroughly registered and biological information and notes of availabeamount of tissue together with a precise location in the cold-store are accessible from adatabase. These specimens are thus available for retrospective analyses or for controlpurposes.

3.3 Number of samples and sampling frequency

In general 10-12 individual specimens from the old Baltic sites (reported to HELCOM) andthe old Swedish westcoast sites (reported to OSPARCOM) are analysed annually from eachsite/species. At the new Baltic and west coast sites 2 pools of 12 individuals are analysedfrom each site/species. For guillemot eggs and perch (old sites), 10 individual specimensare analysed. Organochlorines in blue mussels are analysed in pooled samples containingabout 20 individual specimens in each pool. Since 1996, samples from 12 individualspecimens are analysed which is proposed in the revised guidelines for HELCOM andOSPARCOM.

The sampling recommendation prescribes a narrow age range for sampled species. In a fewcases it has not been possible to achieve the required number of individuals within thatrange. In order to reduce the between-year variation due to sample differences in agecomposition, only specimens within the range of age classes given in brackets after speciesname in the figures, are selected in this presentation.

Sampling is carried out annually in all timeseries. A lower frequency would result in aconsiderable loss in statistical and interpretational power.

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3.4 Sampling season

Sampling of the various fish species and blue mussels is carried out in autumn, outside thespawning season. However, from two sites; Ängskärsklubb and Utlängan, herring is alsosampled in spring. The two spring series started already in 1972. In the beginning onlyorganochlorines where analysed but since 1996 metals have been analysed on a yearly basis.This provides a possibility to study seasonal differences and, when possible, to adjust forthese differences and improve the resolution of the time series. It also gives an opportunitystudy possible changes in the frequencies of spring and autumn spawners.

Guillemot eggs are collected in the beginning-middle of May. A second laid egg (due to alost first egg) should not be collected and are avoided by sampling early laid eggs (see 4.6).

3.5 Sample preparation and registered variables

A short description of the various sampling matrices and the type of variables that areregistered are given below. See TemaNord (1995) for further details.

3.5.1 Fish

For each specimen total body weight, total length, body length, sex, age (see chap. 4 forvarious age determination methods depending on species), reproductive stage, state ofnutrition, liver weight and sample weight are registered.

Muscle samples are taken from the middle dorsal muscle layer. The epidermis andsubcutaneous fatty tissue are carefully removed. Samples of 10 g muscle tissue are preparedfor organochlorine/bromine analysis, 20 g for analysis of PCDD/F and 1.5 g for mercuryanalysis.

The liver is completely removed and weighted in the sample container. Samples of 0.5 – 1gare prepared for metal analyses and 0.5 g for analysis of perfluorinated substances.

3.5.2 Blue mussel

For each specimen total shell length, shell and soft body weight are registered. Trace metalsare analysed in individual mussels whereas samples for organochlorine/brominedetermination and PAH´s are analysed in pools of about 20 specimens.

3.5.3 Guillemot egg

Length, width and total weight are recorded. Egg contents are blown out. Embryo tissue isseparated from the yolk and white that are homogenised.

Weight of the empty and dried eggshell is recorded. The eggshell thickness is measured atthe blowing hole using a modified micrometer.

2 g of the homogenised egg content is prepared for mercury analyses and another to 2 g forthe other analysed metals. 10 g is prepared for analyses of organochlorines/bromines, 30 gfor analysis of PCDD/F and 1 g for perfluorinated substances.

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3.6 Data registration

Data are stored in a flat ASCII file in a hierarchical fashion where each individual specimenrepresents one level. Each measured value is coded and the codes are defined in a code list(Danielsson and Nyberg, 2008). The primary data files are processed through a qualitycontrol program. Suspected values are checked and corrected if appropriate. Data areretrieved from the primary file into a table format suitable for further import to database orstatistical programs.

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4 Sample matrices

The sample database provides the basic information for this report and contains data ofcontaminant concentrations in biota from individual specimens of various species.

Table 4. Number of individual specimen of various species sampled for analysis of contaminants within thebase program

SpeciesN of

individualspecimen %

Herring 4884 50Cod 1052 11Perch 784 8Eelpout 502 5Dab 346 4Flounder 340 3Guillemot 577 6Blue mussel 1218 13Total 9703

4.1 Herring (Clupea harengus)

Herring is a pelagic species that feeds mainly on zooplankton. It becomes sexually matureat about 2-3 years in the Baltic and at about 3-4 years at the Swedish west coast. It is themost dominating commercial fish species in the Baltic. It is important not only for humanconsumption but essential also for several other predators in the marine environment.

Herring is the most commonly used indicator species for monitoring contaminants in biotawithin the BMP (Baltic Monitoring Programme) in the HELCOM convention area and issampled by Finland, Estonia, Poland and Sweden.

Herring muscle tissue is fat and thus very appropriate for analysis of fat-solublecontaminants i.e. hydrocarbons.

Herring samples are collected each year from seventeen sites along the Swedish coasts:Rånefjärden, Harufjärden, Kinnebäcksfjärden (Bothnian Bay), Holmöarna, Örefjärden,Gaviksfjärden, Långvindsfjärden, Ängskärsklubb (Bothnian Sea), Lagnö, Landsort(northern Baltic Proper), Byxelkrok, Abbekås, Hanöbukten, Utlängan (southern BalticProper), Kullen, Fladen (Kattegatt) and at Väderöarna (Skagerack)

Herring liver tissue is analysed for lead, cadmium, copper and zinc. 1995 analyses ofchromium and nickel were added to the programme. Herring muscle tissue is analysed formercury, organochlorines (DDT's, PCB's, HCH's, HCB, PCDD/PCDF), polybrominatedflameretardants and perflourinated substances. Herring muscle from spring caughtspecimens from Ängskärsklubb and Utlängan are analysed for organochlorines and from1996 also for the metals mentioned above. Herring samples from various sites within themarine monitoring programme have also been analysed for dioxins/dibenzofurans, co-planar CB’s, polybrominated diphenyl ethers (Sellström, 1996) and fat composition in pilotstudies. Monitoring of Cs-135 is also carried out on herring from these sites by the SwedishRadiation Protection Institute.

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The herring specimens are age determined by scales. The analysed specimens are femalesbetween 2 - 5 years. Total body weight, liver weight, total length and maturity of gonads isalso recorded.

Table 4.2. The range of weeks when collection of samples has been carried out in all (or almost all) years at aspecific location and the age classes selected in the presented time series below. The 95% confidence intervalsfor the yearly means of total body weight, total length, liver weight and liver and muscle dry weight are alsogiven.

Samplingweek

age bodyweight

length liver weight liver dryweight

muscle dryweight

(year) (g) (cm) (g) (%) (%)

Harufjärden 38-42 3-4 28-31 16-17 0.32-0.39 20-35 22-23Ängskärsklubb 38-42 3-5 33-42 17-18 0.38-0.56 20-35 21-23

- ” - spring 20-24 2-5 25-33 16-17 0.31-0.54 19-23 20-22Landsort 41-48 3-5 38-50 18-20 0.46-0.66 20-32 22-24Karlskrona 41-46 2-4 38-48 17-19 0.36-0.51 22-35 23-25

- ” - spring 18-23 2-3 51-65 19-22 0.30-0.55 17-20 18-20Fladen 35-45 2-3 47-61 19-20 0.55-0.70 22-38 25-27Väderöarna 38-40 2-3 50-90 18-24 0.40-1.0 27-39 24-35

The growth rate varies considerably at the different sites, see Table 4.3 below.

Table 4.3. Average length at the age of three and age at the length of 16 cm at the various sites

Averagelength (cm)at 3 years

Average age(years) at 16

cmHarufjärden 15.91 3.07Ängskärsklubb 16.87 2.24

- ” - spring 16.79 2.42Landsort 17.28 2.17Karlskrona 18.20 1.19Fladen 20.32 0.82Väderöarna 21.73 0.53

4.2 Cod (Gadus morhua)

The Baltic cod lives below the halocline feeding on bottom organisms. It becomes sexuallymature when 2-6 years old in Swedish waters. The spawning takes place during the periodMay - August (occasionally spawning specimens could be found in March or September).The cod requires a salinity of at least 11 PSU and an oxygen content of at least 2 ml/l(Nissling, 1995) for the spawning to be successful. The population shows great fluctuationsand has decreased dramatically during the period 1984-1993. Cod fishing for humanconsumption is economically important.

Cod is among the ‘first choice species’ recommended within the JAMP (Joint Assessmentand Monitoring Programme) and BMP (Baltic Monitoring Programme).

Cod is collected in the autumn from two sites: south east of Gotland and from Fladen at theSwedish west coast. Cods are age determined by otoliths. Specimens of both sexes, between3-4 years from Gotland and between 2-4 years from Fladen, are analysed.

The cod liver is fat and organic contaminants are often found in relatively highconcentrations. For that reason, it is a very appropriate matrix for screening for ‘new’contaminants.

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Cod liver tissue is analysed for lead, cadmium, copper and zinc as well as for organo-chlorines. 1995 analyses of chromium and nickel were added and analysis for brominatedsubstances and HBCD in 1999. Cod muscle tissue is analysed for mercury.

Before 1989, 20 individual samples from south east of Gotland and 25 samples fromKattegatt were analysed for organochlorines. Between 1989-1993 one pooled sample fromeach site, each year was analysed. Since 1994, 10 individual cod samples are analysed at thetwo sites each year.

Table 4.4. The range of weeks when collection of samples has been carried out in all (or almost all) years at aspecific location, the age classes selected in the presented time series below. The 95% confidence intervals forthe yearly means of total body weight, total length, liver weight and liver dry weight are also given.

Samplingweek

age bodyweight

Length liverweight

liver dryweight

(year) (g) (cm) (g) (%)

SE Gotland 35-39 3-4 310-455 32-35 16-41 53-63Fladen 37-42 2-3 240-345 29-33 4-10 33-44

4.3 Dab (Limanda limanda)

Dab is a bottom living species feeding on crustaceans, mussels, worms, echinoderms andsmall fishes. The males become sexually mature between 2-4 years and the femalesbetween 3-5 years. The spawning takes place during the period April – June shallow coastalwaters. The dab tends to migrate to deeper water in late autumn.

Dab is among the ‘first choice species’ recommended within the JAMP (Joint Assessmentand Monitoring Programme).

Because of reduced analytical capacity, organochlorines in dab were annually analysed inone pooled sample from 1989 to 1995. Since 1995 samples of dab are no longer analysedbut are still collected and stored in the Environmental Specimen Bank.

Dab is collected from Kattegatt (Fladen) in the autumn. Liver tissue samples have beenanalysed for lead, cadmium, copper and zinc and muscle tissue samples for organochlorinesand mercury. The dab specimens are age determined by otoliths. Specimens between 3-5years have been analysed.

Table 4.5. The range of weeks when collection of samples has been carried out in all (or almost all) years, theage classes selected in the presented time series below. The 95% confidence intervals for the yearly means oftotal body weight, total body length, liver weight and liver dry weight are also given.

Samplingweek

age bodyweight

length liverweight

liver dryweight

(year) (g) (cm) (g) (%)

Fladen 37-44 2-6 50-250 15-30 0.5-2 20-40

4.4 Flounder (Platichtys flesus)

Flounder is a bottom living species feeding on crustaceans, mussels, worms, echinodermsand small fishes. The males in the Skagerack become sexually mature between 3-4 years ofage and the females one year later. The spawning in the Skagerack takes place during theperiod January – April in shallow coastal waters. The flounder tends to migrate to deeperwaters in late autumn.

Flounder is among the ‘second choice species’ recommended within the JAMP (JointAssessment and Monitoring Programme).

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Because of reduced analytical capacity, organochlorines in flounder were annually analysedin one pooled sample from 1989 to 1995. Since 1995 samples of flounder are no longeranalysed but are still collected and stored in the Environmental Specimen Bank.

Flounder is collected from the Skagerack (Väderöarna) in the autumn. Liver tissue sampleshave been analysed for lead, cadmium, copper and zinc and muscle tissue samples fororganochlorines and mercury. The flounder specimens are age determined by otoliths.Specimens between 4-6 years have been analysed.

Table 4.6. The range of weeks when collection of samples has been carried out in all (or almost all) years, theage classes selected in the presented time series below. The 95% confidence intervals for the yearly means oftotal body weight, total body length, liver weight and liver dry weight are also given.

Samplingweek

age bodyweight

length liverweight

liver dryweight

(year) (g) (cm) (g) (%)

Väderöarna 37-44 3-6 100-400 20-35 1-5 18-30

4.5 Blue mussel (Mytilus edulis)

Blue mussels are one of the most common used organisms for monitoring contaminants inbiota. Adult mussels are sessile and hence it is easier to define the area the samplesrepresent, compared to fish.

Blue mussel is among the ‘first choice species’ recommended within the JAMP (JointAssessment and Monitoring Programme).

Blue mussels are collected from the Kattegatt (Fladen, Nidingen), from the Skagerack(Väderöarna) and from Kvädöfjärden in the Baltic Proper. The mussels are sampled in theautumn. Sampling depth varies between the sampling sites.

Soft body tissue is analysed for lead, cadmium, copper, zinc, mercury and organochlorines.In 1995 analyses of chromium and nickel were added and in 2000 analysis of brominatedsubstances. From 1995 samples from Kvädöfjärden were included in the analysis. Hitherto,samples from this site had only been collected and stored (since 1981). Organochlorines inblue mussels are analysed in pooled samples from each site and year whereas the tracemetals are analysed in 25 individual samples per year and site (15 from 1996). PAH´s hasbeen analysed retrospectively (start 1984/87) in mussels from all three localities and aresince 2003 analysed on a yearly basis in pooled samples.

Table 4.7. The range of weeks when collection of samples has been carried out in all (or almost all) years at aspecific location, the shell length interval selected in the presented time series below. The 95% confidenceintervals for the yearly means of soft body weight and shell weight are also given.

Samplingweek

Samplingdepth

shelllength

shellweight

softbody

weight(m) (cm) (g) (g)

Kvädöfjärden 38-43 2-10 2-3 0.4-0.6 1-2Fladen, Nidingen 37-51 0.5 5-8 5-25 2-10Väderöarna 42-51 2 6-10 10-30 5-25

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4.6 Guillemot (Uria aalge)

Guillemots are appropriate for monitoring of contaminants in the Baltic Sea since most ofthem do not migrate further than to the southern parts of the Baltic proper during the winterseason. They feeds mainly on sprat (Sprattus sprattus) and herring (Clupea harengus). Theguillemot breed for the first time at the age of 4-5 years and the egg is hatched after about32 days.

The egg content is fat (11-13%) and thus very appropriate for analysis of fat-solublecontaminants i.e. hydrocarbons.

Normally the guillemot lay just a single egg but if this egg is lost, it may lay another. It hasbeen shown that late laid eggs of guillemot contain significantly higher concentrations oforganochlorines compared to early laid eggs (Bignert et al., 1995). In this presentation onlyearly laid eggs are included except for dioxins where the results from all collected eggs areincluded. 10 guillemot eggs, collected between week 19-21(22), are analysed each year.

Guillemot egg contents from St Karlsö are analysed for mercury and organochlorines. From1996, the concentrations of Pb, Cd, Ni, Cr, Cu and Zn are also analysed. The timeserver hasalso been analysed for PCC (Wideqvist et al. 1993), dioxins/dibenzofurans, perflourinatedcompounds (Holmström et al., 2005) and polybrominated compounds (Sellström, 1996).Various shell parameters e.g. shell weight, thickness and thickness index is also monitored.The weights of several hundreds of fledglings are normally recorded each year at St Karlsö.Eggs have also been collected for some years from Bonden in the northern parts of theBothnian Sea but so far only results (organochlorines) for 1991 are available.

4.7 Perch (Perca fluviatilis)

Perch is an omnivorous, opportunistic feeding predatory fish. Male perch become sexuallymature between 2-4 years and the females between 3-6 years of age. The spawning takesplace during the period April - June when the water temperature reaches about 7-8 degrees.Perch muscle tissue is lean and contains only about 0.8% fat.

Integrated monitoring with fish physiology and population development is running on perchin co-operation with the University of Gothenburg and the Swedish Board of Fisheries.Perch is also used as an indicator species for contaminant monitoring within the nationalmonitoring programme of contaminants in freshwater biota.

Perch muscle tissue samples from two coastal sites, Holmöarna and Kvädöfjärden in theBaltic, are analysed for organochlorines and mercury. In 1995 analyses of lead, cadmium,chromium, nickel, copper and zinc in perch liver were added to the programme and in 2006PCDD/F.

Table 4.8. The range of weeks when collection of samples has been carried out in all (or almost all) years at aspecific location, the age classes selected in the presented time series below. The 95% confidence intervals forthe yearly means of total body weight, total body length, liver weight and liver dry weight are also given.

Perch Samplingweek

age bodyweight

length liverweight

(year) (g) (cm) (g)

Holmöarna 33-42 3-5 77-88 17-21 0.86-1.5Kvädöfjärden 31-40 3-5 56-67 15-20 0.50-0.73

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4.8 Eelpout, viviparous blenny (Zoarces viviparus)

The eelpout is considered as a more or less stationary species living close to the bottom,feeding on insect larvae, molluscs, crustaceans, worms, hard roe and small fishes. Itbecomes sexually mature when 2 years old at a length of 16 - 18 cm. The spawning takesplace during August - September. After 3-4 weeks the eggs hatch inside the mothers bodywhere the fry stay for about three months. The possibility to measure the number of eggs,fertilized eggs, the size of the larvae and the embryonic development makes the speciessuitable for integrated studies of contaminants and reproduction (Jacobsson et al., 1993).Integrated monitoring with fish physiology and population development is running oneelpout in co-operation with the University of Gothenburg and the Swedish Board ofFisheries.

Eelpout specimens have been collected from Väderöarna in the Skagerack since 1988. Inthis time series analyses of various PCB congeners are available. Since 1995, eelpout is alsocollected from Holmöarna and Kvädöfjärden. Liver tissue is analysed for lead, cadmium,chromium, nickel, copper and zinc whereas muscle tissue is analysed for mercury andorganochlorines.

Table 4.9. The range of weeks when collection of samples has been carried out in all (or almost all) years at aspecific location, the age classes selected in the presented time series below. The 95% confidence intervals forthe yearly means of total body weight, total body length, liver weight and liver and muscle dry weight are alsogiven.

Samplingweek

age totalweight

length liver weight liver dryweight

muscle dryweight

(year) (g) (cm) (g) (%) (%)

Holmöarna 47 3-6 21-26 18-20 0.20-0.50 13-26 17-21Kvädöfjärden 46 3-6 28-39 19-22 0.20-0.60 18-25 17-20Väderöarna (36), 45-47 3-6 35-70 20-25 0.40-1.00 14-32 18-20

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5 Sampling sitesThe location and names of the sample sites are presented in Figure 5. The sampling sites arelocated in areas regarded as locally uncontaminated and, as far as possible, uninfluenced bymajor river outlets or ferry routes and not too close to heavy populated areas.

The Swedish sampling stations are included in the net of HELCOM stations in the Balticand in the Oslo and Paris Commissions’ Joint Monitoring Programme (OSPAR, JMP)station net in the North Sea. Finland has one site in the Bothnian Bay, four sites in theBothnian Sea and three in the Gulf of Finland i.e. altogether eight sites from which data isreported to HELCOM. Poland has three sites along the Polish coast. Denmark submits tracemetal data from three sites. Data of contaminants in biota from Russia, Estonia, Latvia,Lithuania or Germany has not yet been assessed within HELCOM. Within JMP time seriesof various contaminants in biota are reported from Belgium (3 sites, both OC’s and heavymetals), Denmark (2, heavy metals), France (7, heavy metals), Germany (22, both), Iceland(12), The Netherlands (12), Norway (41), Spain (7), Sweden (2) and UK (2).

During 2007 the monitoring programme has been expanded, herring from 10 new sites havebeen added. Name and location of these sites are found at the map below.

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12

3

45

6

7

8

9

2221 10

11

20 12 1319

14

18

1516

17

200 km

TISS - 08.03.31 16:43, stat_sc

Figure 5. Sampling sites within the National Monitoring Programme in Marine. 1) Rånefjärden,2) Harufjärden, 3) Kinnbäcksfjärden, 4) Holmöarna, 5) Örefjärden, 6) Gaviksfjärden, 7) Långvindsfjärden,8) Ängskärsklubb, 9) Lagnö, 10) Landsort, 11) Kvädöfjärden, 12) Byxelkrok, 13) St.Karlsö, 14) SE Gotland,15) Utlängan, 16) V. Hanöbukten, 17) Abbekås, 18) Kullen, 19) Fladen, 20) Nidingen, 21) Väderöarna,22) Fjällbacka

5.1 Rånefjärden, Bothnian Bay, north

Co-ordinates: 65 45’ N, 22 25’ E within a radius of 3’, ICES 60H2 93County: Norrbottens län

Surface salinity: <3 PSUAverage air temperature: January: -10 / April: -1 / July: 15 / October: 2

Sampling matrix: Baltic herring and perch (only sampling), autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´s.

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5.2 Harufjärden, Bothnian Bay, north

Co-ordinates: 65 35’ N, 22 53’ E within a radius of 3’, ICES 60H2 93County: Norrbottens län

Surface salinity: <3 PSUAverage air temperature: January: -10 / April: -1 / July: 15 / October: 2

Sampling matrix: Baltic herring, autumnStart: 1978 DDT/PCB, 1980 Hg, 1982 Pb/Cd/Cu/Zn, 1988 HCH’s/HCB, 1995 Cr/Ni

5.3 Kinnebäcksfjärden, Bothnian Bay

Co-ordinates: 64 50’ N, 21 16’ E within a radius of 3’, ICES 58H1County: Norrbottens län

Average air temperature: January: -10 / April: -1 / July: 15 / October: 2

Sampling matrix: Baltic herring and perch, autumnStart: Only sampling

5.4 Holmöarna, Bothnian Bay, south, coastal site

Co-ordinates: 63 41’ N, 20 53’ E, ICES 56H0County: Västerbottens län

Surface salinity: c 4 PSUAverage air temperature: January: -5 / April: 0 / July: 15 / October: 4

Start year for various contaminants and species:

Contaminant/ Species PCB/DDT HCH/HCB Hg Pb/Cd/Cu/Zn Cr/Ni PCDD/FPerch 1980 19(89)95 19(91)95 1995 1995 2007Eelpout 1995 1995 1995 1995 1995

Both species are collected during the autumn. Baltic herring is also sampled (since 2007).

At Holmöarna the contaminant monitoring is integrated with fish population and -physiologymonitoring, carried out by the Swedish Board of Fisheries and the University of Gothenburg.

5.5 Örefjärden, Bothnian Bay, south

Co-ordinates: 63 25’ N, 19 24’ E within a radius of 3’, ICES 55G9County: Västernorrlands län


Sampling matrix: Baltic herring and perch, autumnStart: Only sampling

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5.6 Gaviksfjärden, Bothnian Bay, south

Co-ordinates: 63 07’ N, 18 38’ E within a radius of 3’, ICES 55G8County: Västernorrlands län


Sampling matrix: Baltic herring and perch 8only sampling), autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´s

5.7 Långvindsfjärden, Bothnian Sea

Co-ordinates: 61 46’ N, 17 27’ E within a radius of 3’, ICES 52G7County: Gävleborgs län

Average air temperature: January: -3 / April: 2 / July: 15 / October: 6

Sampling matrix: Baltic herring and perch (only sampling), autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´s

5.8 Ängskärsklubb, Bothnian Sea

Co-ordinates: 60 44’ N, 17 52’ E, ICES 50G7 83County: Gävleborgs län / Uppsala län


Sampling matrix: Baltic herring, spring/autumnStart, spring: 1972 DDT/PCB, 1972-75 Hg, 1988 HCH’s/HCB, 1979 PCDD/F, 2005 PFC

Start, autumn: 1978 DDT/PCB, 1980 Hg, 1982 Pb/Cd/Cu/Zn, 1988 HCH’s/HCB, 1995 Cr/Ni, 1994PBDE/HBCD,1979 PCDD/F, 2005 PFC

In 1996 collection and analyses of herring samples from four other sites in the region werefinanciated by the county board of Gävleborgs län. This investigation is valuable to estimate therepresentativeness of the well established sample site at Ängskärsklubb. It also gives informationon small scale geographical variation in general.

5.9 Lagnö, Baltic Proper, north

Co-ordinates: 5 9 25’ N, 18 37’ E, ICES 47G8County: Stockholms län

Surface salinity: c 6-7 PSUAverage air temperature: January: -1 / April: 3 / July: 16 / October: 7

Sampling matrix: Baltic herring and perch (only sampling), autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´s

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5.10 Landsort, Baltic Proper, north

Co-ordinates: 58 42’ N, 18 04’ E, ICES 46G8 23County: Stockholms län / Södermanlands län


Sampling matrix: Baltic herring, autumnStart: 1978 DDT/PCB, 1981 Hg, 1982 Pb/Cd/Cu/Zn; 1988, HCH’s/HCB; 1995 Cr/Ni, 1995PBDE/HBCD, 2005 PCDD/F and PFC

Herring samples have also been collected to analyse the metallothionein concentration and tocompare the fat composition in old versus young herring specimen.

5.11 Kvädöfjärden, Baltic Proper, coastal site

Co-ordinates: 58 2’ N, 16 46’ E, ICES 45G6County: Östergötland / Kalmar



Contaminant/ Species PCB/DDT HCH/HCB Hg Pb/Cd/Cu/Zn Cr/Ni PAH PCDD/FPerch 1980 19(84)90 1981 1995 1995 2007Blue mussel 1995 1995 1995 1995 1995 1987Eelpout 1995 1995 1995 1995 1995

All species are collected during the autumn.

At Kvädöfjärden the contaminant monitoring is integrated with fish population and -physiologymonitoring, carried out by the Swedish Board of Fisheries and the University of Gothenburg.

Neuman et al. (1988) report decreasing Secchi depths during the invested period; somewhat below6 m 1980 to somewhat above 4 m in the middle of the eighties.

5.12 St Karlsö, Baltic Proper

Co-ordinates: 57 19’ N, 17 309’ E, ICES 43G6County: Kalmar län

Surface salinity: c 7 PSUAverage air temperature: January: 0 / April: 3 / July: 16 / October: 8

Sampling matrix: Baltic herring, autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´s

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5.13 St Karlsö, Baltic Proper

Co-ordinates: 57 11’ N, 17 59’ E, ICES 43G7 County: Gotland

St Karlsö is situated about 7 km west of the island Gotland and about 80 km east of the SwedishBaltic coast.


Sampling matrix: Guillemot egg, MayStart: 1968 DDT/PCB, 1969 Hg, 1988 HCH’s/HCB

5.14 South east of Gotland, Baltic Proper

Co-ordinates: 56 53’ N / 18 38’ E, ICES 42G8 43 County: Gotland

Surface salinity: c 7-8 PSUAverage air temperature: January: 0 / April: 3 / July: 16 / October: 8

Sampling matrix: Cod, autumnStart: 1980 DDT/PCB/Hg, 1982 Pb/Cd/Cu/Zn, 1988 HCH’s/HCB, 1995 Cr/Ni, 1999 PBDE/HBCD

5.15 Utlängan, Karlskrona archipelago, Baltic Proper, south

Co-ordinates: 55 57’ N, 15 47’ E, ICES 40G5 73County: Blekinge


Start year for analysis of various contaminants in herring spring/autumn:

Contaminant/Species

PCB/DDT HCH/HCB Hg Pb/Cd/Cu/Zn

Cr/Ni PBDE/HBCD

PCDD/F PFC

Herring, spring 1972 1988 1972-75,95 1995 1995 2000 2000 2005Autumn 1979 1988 1981 1982 1995 2000 2000 2005

In 1997 collection and analyses of herring samples from one site rather close to the reference siteand two sites in Hanöbukten were financiated by the Environmental Protection Agency. Thisinvestigation is valuable to estimate the representativeness of the well-established sample site atUtlängan. It will also give information on small-scale geographical variation in general.

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5.16 Västra Hanöbukten, Baltic Proper, south

Co-ordinates: 55 45’ N, 14 17’ E, ICES 40G4County: Skåne


Sampling matrix: Baltic herring, autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´s

5.17 Abbekås, Baltic Proper, south

Co-ordinates: 55 18’ N, 13 36’ E, ICES 39G3County: Skåne


Sampling matrix: Baltic herring, autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´

5.18 Kullen, Kattegatt, Swedish west coast

Co-ordinates: 56 19’ N / 12 23’ E, ICES 41G2County: Skåne


Sampling matrix: Herring, autumnStart: 2007 DDT/PCB, Hg, Pb/Cd/Cu/Zn/Cr/Ni, HCH’s/HCB, PBDE/HBCD, PCDD/F and PFC´

5.19 Fladen, Kattegatt, Swedish west coast

Co-ordinates: 57 14’ N / 11 50’ E, ICES 43G1 83, JMP J34County: Halland



Contaminant/Species

PCB/DDT HCH/HCB Hg Pb/Cd/Cu/Zn

Cr/Ni PAH PBDE/HBCD

PCDD/F PFC

Herring 1980 1988 1981 1981 1995 1999 1997 2005Cod 1979 1988 1979 1981 1995 1999Dab 1981 1988 1981 1981 -Blue mussel 1984 1988 1981 1981 1995 1985

All species are collected during the autumn.

Since 1987 blue mussels have been collected at Nidingen about 10 km NNE of Fladen.

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5.20 Väderöarna, Skagerack, Swedish west coast

Co-ordinates: 58 31’ N, 10 54’ E ICES 46G0 93, JMP J33County: Göteborgs- o Bohus län



Contaminant/ Species

PCB/ DDT HCH/ HCB Hg Pb/Cd/Cu/Zn

Cr/Ni PAH PBDE/HBCD

PCDD/F PFC

Herring 1995 1995 1995 1995 1995 1999 2007 2005Eelpout 1995 1995 1995 1995 1995Flounder 1980 1988 1980 1981 -Blue mussel 1984 1988 1980 1981 1995 1985

Eelpout and blue mussels are collected at Musön, Fjällbacka at the coast (about 10 km east ofVäderöarna). All species are collected during the autumn.

5.21 Bonden, northern Bothnian Sea

Co-ordinates: 63 25’ N, 20 02’ E, ICES 55H0County: Västerbotten


Sampling matrix: Guillemot egg (only rotten eggs), summerStart: 1991 DDT/PCB

The collection of egg samples has been more or less sporadic however, since the populationdevelopment has been low.

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6 Analytical methods

6.1 Trace metals

The analyses of trace metals are carried out at the Department of EnvironmentalAssessment at Swedish University of Agricultural Sciences. Analytical methods for metalsin liver are described by Borg et al., 1981, for mercury by May & Stoeppler, 1984, andLindsted & Skare,1971. The laboratory participates in the periodic QUASIMEMEintercallibration rounds. It has also participated in the programme for sampling qualitycontrol, QUASH

CRM’s used for mercury are:DORM-2: 1994-1997and for the other metals:DOLT-1: 1990-1991, DOLT-2: 1993-1997 and Bovine Liver B.L 1577b: 1997, TORT-2:1997

Due to a change of method for metal analysis in 2004, values after 2003 are not presented inthis section. The new method is under investigation, since the values are uncertain.

6.2 Organochlorines and brominated flame retardants

The analyses of organochlorines and brominated flame retardants are carried out at theLaboratory for Analytical Environmental Chemistry at the Institute of AppliedEnvironmental Research (ITM) at Stockholm University. The analytical methods appliedare described elsewhere. The organochlorines are presently determined by high resolutiongas chromatography (Jensen /et al./, 1983, Eriksson /et al/., 1994). The brominatedsubstances are analysed by GC connected to a mass spectrometer operating in the electroncapture /negative ion mode (Sellström et al., 1998). This year a few complementary analysisconcerning the higher brominated substances BDE 196, 197, 203, 205, 206, 207 and 209 inherring from Harufjärden has been carried out. The analyse is similar to the one for thelower brominated ones except for the use of a shorter column, 15m, with a thinner phase,0.1mm.

6.2.1 Quality assurance

The Quality control for organochlorines has continuously improved the last ten years andresulted in an accreditation 1999. Assessment is performed once a year by the accreditationbody SWEDAC and was last done in the autumn of 2007. The laboratory is fulfilling theobligation in SS-EN ICO/IEC 17025.The accreditation is valid for CB 28, 52, 101, 118,153, 138, 180, DDEpp, DDDpp, DDTpp, HCB and a- b- y-HCH in biological tissues. Sofar the brominated flame retardants (BFRs) are not accredited but the analysis of BDE 47,99,100, 153, 154 and HBCD are in many ways performed with the same quality aspects asthe organochlorines.

The Quality Assurance program is built on the Quality Manual, SOPs and supplements. Theannual audit includes a review of the qualifications of the staff, internal quality audit

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(vertical), SOPs, internal quality controls, filing system, proficiency testing, up-to-daterecord of the training of the staff (to be able to perform their assigned tasks), accreditedmethods and audit of the quality program.

6.2.2 Standards

The original of all standards are certified with known purity and precision. Theconcentrations are calculated for each individual congener. In April 2005 a new PBDE-standard as well as HBCD-standard was introduced. The standards were made fromsolutions where the concentrations of each compound had lower uncertainty (±5%)compared with the old standards (±10%).

6.2.3 Detection limits and the uncertainly in the measurements

The uncertainty in the measurement is found to follow the theory stated by Horwitz in 1982.With increasing level follows decreasing relative standard deviation (Horwitz et al., 1989).These relative standard deviations are calculated from 6321 PCB and pesticides values fromcontrol samples during 15 years. The uncertainly in the measurements is expressed as tworelative standard deviations and is less than 36% in the interval 0.04-0.5 ng/g, less than 22%in the interval 0.5-5 ng/g and less than 16% when higher than 5 ng/g. The uncertainly in themeasurements for BFRs is expressed in the same way as for the PCBs, and are in the samerange (20-36%) in the interval 0.005-5 ng/g. The standard deviation for the five BDEs andHBCD are calculated from 1240 values from control samples during 8 years.

Detection limits and other comments are reported under each contaminant description.

6.2.4 Validation

To have the possibility to control impurities in solvents, equipments and glasswares, oneblank sample is extracted together with each batch of environmental samples.

Coeluation of congeners in GC analysis is dependent upon instrumental conditions such ascolumn type, length, internal diameter, film thickness and oven temperature etc. Somepotentially coeluting PCB congeners on a column with the commonly used phase DB-5 areCB-28/-31, CB-52/-46/-49, CB-101/-84/-90, CB-118/-123/-149,CB-138/-158/-163,

CB-153/-132/-105 and CB-180/-193 (Schantz et al., 1993). To minimize those problems acolumn with a more polar phase is used in parallell.

Coeluation with other PCBs then the seven can then be avoided on at least one column,with the exception for CB-138, which coelutes with

CB-163 (Larsen et al., 1990). Therefore CB-138 is reported as CB-138+163.

In order to verify possibly coelutions with HCHs, DDTpp and DDDpp one representativesample extract are also treated with potassium hydroxide after the treatment with sulphuric

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acid. The two extracts are analysed and the chromatograms compared. No remaining peaksat the same retention time as the analytes indicates no coelutions.

When introducing a new matrix one of the samples is re-extracted with a mixture of morepolar solvents for control of no remaining contaminants in the matrix residual. Samplesfrom new matrixes and samples from already established matrixes from new samplinglocation are also examined for suitable internal standard.

From 2005 to 2008 ITM took part in the EU project NORMAN where one of the issues ofthe project was to provide protocols for validation for harmonisation and dissemination ofchemical monitoring methods and a final version of this protocol can be find on the websitewww.norman-network.net.

During 2008 the laboratory has moved into a new building. The analysis of bothorganochlorines and BFRs has been validated with respect to blank samples and re-analysedold samples with good results.

6.2.5 Reference Material

Two laboratory reference materials (LRM) are used as extraction controls, chosen withrespect to their lipid content and level of organic contaminants. The controls consist ofherring respectively salmon muscle, homogenised in a household mixer and stored inaliquots of 10 gram of herring respectively 3 gram of salmon in air tight bags of aluminiumlaminate at -80°C. At every extraction event one extraction control is extracted as well.From 1998 CRM 349, cod lever oil was analysed twice a year for PCBs. During 2003 thelaboratory changed to CRM 682 and 718, mussel (whole body) respectively herring(muscle), being better representants since they cover the whole extraction procedure. One ofthose samples are analysed once a year. Until now no CRM exist for BFRs.

6.2.6 Intercalibration and certifications

Concerning PCBs and pesticides, the laboratory has participated in the periodicQUASIMEME intercalibration exercise since 1993, with two rounds every year, each onecontaining two samples. 565 of the 591 values that the laboratory has produced during theyears have been satisfactory according to QUASIMEME, meaning they have falling within+/- 2 sd of the assigned value. In 2000, the laboratory participated in the first interlaboratorystudy ever performed for BFR and since 2001 the BFRs are incorporated in theQUASIMEME scheme. From the beginning there was one yearly exercise but after 2006this was changed to two exercises per year with one sample each time. The laboratory hasperformed with good results for these studies until 2007. The reason for this less goodperformance was limited access to the instrument, with not enough time for cleaning andpre-tests. However, during 2008 a new instrument has been bought and validated. The twofollowing intercalibration exercises have shown improved results. As a total, 59 of the 73values the laboratory has produced during the years have been satisfactory according toQUASIMEME.The laboratory has since 1998 participating in three certification exercises, concerningPCBs, pesticides and BFRs. In two of this the laboratory was involved as a co-organizer. Asa total, 494 of the 534 reported values were accepted and could be used as a part of the

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certification. The laboratory has also participated in the programme for sampling qualitycontrol, QUASH.

6.3 Dioxins, dibenzofurans and dioxinlike PCB´s

The analyses of dioxins and dioxin-like PCBs are carried out at the Department ofChemistry, Umeå University. The extraction method is described by Wiberg et al.,1998, theclean-up method by Danielsson et al. 2005, and the instrumental analysis (GC-HRMS) byLiljelind et al. 2003. The laboratory participates in the annual FOOD intercallibrationrounds, and include a laboratory reference material (salmon tissue) with each set ofsamples.

6.4 Perfluorinated substances

The analyses of perfluorinated substances are carried out at the Analytical EnvironmentalChemistry Unit at the Department of Applied Environmental Science (ITM), University ofStockholm.

6.4.1 Sample preparation and instrumental analysis

A sample aliquot of approximately 0.5 g homogenized tissue was spiked with 5 ng each of asuite of mass-labelled internal standards (13C-labelled perfluorinated sulfonates andcarboxylic acids). The samples were extracted twice with 5 mL of acetonitrile in anultrasonic bath. Following centrifugation, the supernatant extract was removed and thecombined acetonitrile phases were concentrated to 1 mL under a stream of nitrogen. Theconcentrated extract underwent dispersive clean-up on graphitized carbon and acetic acid.Approximately 0.5 mL of the cleaned-up extract was added to 0.5 mL of aqueousammonium acetate. Precipitation occurred and the extract was centrifuged before the clearsupernatant was transferred to an autoinjector vial for instrumental analysis and the volumestandards BTPA and bPFDcA were added.

Aliquots of the final extracts were injected automatically on a high performance liquidchromatography system (HPLC; Alliance 2695, Waters) coupled to a tandem massspectrometer (MS-MS; Quattro II, Micromass). Compound separation was achieved on anAce 3 C18 column (150 x 2.1 mm, 3 m particles, Advanced ChromatographyTechnologies) with a binary gradient of ammonium acetate buffered methanol and water.The mass spectrometer was operated in negative electrospray ionization mode with thefollowing optimized parameters: Capillary voltage, 2.5 kV; drying and nebuliser gas flow(N2), 300 and 20 L/h, respectively; desolvation and source temperature, 150 and 120 C,respectively. Quantification was performed in selected reaction monitoring chromatogramsusing the internal standard method.

6.4.2 Quality control

The extraction method employed in the present study (with the exception of theconcentration step) has previously been validated for biological matrices and showedexcellent analyte recoveries ranging between 90 and 110% for PFCAs from C6 to C14

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(Powley and Buck, 2005). Including extract concentration, we determined recoveriesbetween 70 and 90% for C6- to C10-PFCAs and 6570% for C11-C14 PFCAs. Extractionefficiencies for perfluorosulfonates (PFSs), including perfluorooctane sulfonamide(PFOSA), were determined to 7095%. Furthermore, mean method recoveries of the masslabelled internal standard compounds were between 52% and 102%. Method quantificationlimits (MQLs) for all analytes were determined on the basis of blank extraction experimentsand ranged between 0.2 and1.0 ng/g wet weight (w.w.) for the different compounds. Twoherring liver samples were analysed in duplicates in different batches on different days. Theobtained values varied <15% for all of the 14 paired results (7 detected analytes in twosamples). A fish tissue sample used in an international inter-laboratory comparison (ILC)study in 2007 (van Leeuwen et al., 2009) was analyzed along with the samples. Theobtained concentrations deviated from the mean concentration from the ILC study by lessthan 10% for all 7 compounds quantified in the ILC.

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7 Statistical treatment,graphical presentation

7.1 Trend detection

One of the main purposes of the monitoring programme is to detect trends. The trenddetection is carried out in three steps.

7.1.1 Log-linear regression analyses

Log-linear regression analyses are performed for the entire investigated time period andalso for the recent ten years for longer time series.

The slope of the line describes the yearly percentual change. A slope of 5% implies that theconcentration is halved in 14 years whereas 10% corresponds to a similar reduction in 7years and 2% in 35 years. See table 7.1 below.

Table 7.1. The approximate number of years required to double or half the initial concentration assuming acontinuous annual change of 1, 2, 3, 4, 5, 7, 10, 15 or 20% a year.

1% 2% 3% 4% 5% 7% 10% 12% 15% 20%

Increase 70 35 24 18 14 10 7 6 5 4Decrease 69 35 23 17 14 10 7 6 4 3

7.1.2 Non-parametric trend test

The regression analysis presupposes, among other things, that the regression line gives agood description of the trend. The leverage effect of points in the end of the line is also awell-known fact. An exaggerated slope, caused 'by chance' by a single or a few points in theend of the line, increases the risk of a false significant result when no real trend exist. Anon-parametric alternative to the regression analysis is the Mann-Kendall trend test(Gilbert, 1987, Helsel & Hirsch,1995, Swertz,1995). This test has generally lower powerthan the regression analysis and does not take differences in magnitude of theconcentrations into account; it only counts the number of consecutive years where theconcentration increases or decreases compared with the year before. If the regressionanalysis yields a significant result but not the Mann-Kendall test, the explanation could beeither that the latter test has lower power or that the influence of endpoints in the time serieshas become unwarrantable great on the slope. Hence, the eighth line reports Kendall's '',and the corresponding p-value. The Kendall's '' ranges from 0 to 1 like the traditionalcorrelation coefficient ‘r’ but will generally be lower. ‘Strong’ linear correlations of 0.9 orabove corresponds to -values of about 0.7 or above (Helsel and Hirsch, 1995, p. 212). Thistest was recommended by the Swedish EPA for use in water quality monitoringprogrammes with annual samples, in an evaluation comparing several other trend tests(Loftis et al. 1989).

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7.1.3 Non-linear trend components

An alternative to the regression line in order to describe the development over time is a kindof smoothed line. The smoother applied here is a simple 3-point running mean smootherfitted to the annual geometric mean values. In cases where the regression line is badly fittedthe smoothed line may be more appropriate. The significance of this line is tested by meansof an Analysis of Variance where the variance explained by the smoother and by theregression line is compared with the total variance. This procedure is used at assessments atICES and is described by Nicholson et al., 1995.

7.2 Adjustments for covariables

It has been shown that metal concentrations in cod liver are influenced by fat content(Grimås et. al., 1985). Consequently the metal concentrations in cod liver are adjusted forfat content. In some occasions (when the average fat content differs between years) this is ofmajor importance and might change the direction of the slope and decrease the between-year variation considerable. For the same reasons, mercury concentrations are adjusted forbody weight and organochlorines in spring caught herring muscle tissue are adjusted for fatcontent (Bignert et. al., 1993) where appropriate (indicated in the header text of the figures).

7.3 Outliers and values below the detection limit

Observations further from the regression line than what is expected from the residualvariance around the line is subjected to special concern. These deviations may be caused byan atypical occurrence of something in the physical environment, a changed pollution loador errors in the sampling or analytical procedure. The procedure to detect suspected outliersin this presentation is described by Hoaglin and Welsch (1978). It makes use of the leveragecoefficients and the standardised residuals. The standardised residuals are tested against at.05 distribution with n-2 degrees of freedom. When calculating the ith standardised residualthe current observation is left out implying that the ith observation does not influence theslope nor the variance around the regression line. The suspected outliers are merelyindicated in the figures and are included in the statistical calculations except in a few cases,pointed out in the figures.

Values reported below the detection limit is substituted using the ‘robust’ method suggestedby Helsel & Hirsch (1995) p 362, assuming a log-normal distribution within a year.

7.4 Legend to the plots

The analytical results from each of the investigated elements are displayed in figures. Aselection of sites and species are presented in plots, time series shorter than 4 years.

The plot displays the geometric mean concentration of each year (circles) together with theindividual analyses (small dots) and the 95% confidence intervals of the geometric means.

The overall geometric mean value for the time series is depicted as a horizontal, thin line.

The trend is presented by one or two regression lines (plotted if p < 0.10, two-sidedregression analysis); one for the whole time period in red and one for the last ten years in

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pink (if the time series is longer than ten years). Ten years is often too short a period tostatistically detect a trend unless it is of considerable magnitude. Nevertheless the ten yearregression line will indicate a possible change in the direction of a trend. Furthermore, theresidual variance around the line compared to the residual variance for the entire period willindicate if the sensitivity have increased as a result of e.g. an improved sampling techniqueor that problems in the chemical analysis have disappeared.

A smoother is applied to test for non-linear trend components (see 7.1.3). The smoothedline in blue is plotted if p < 0.10. A broken line or a dashed line segment indicates a gap inthe time series with a missing year.

The log-linear regression lines fitted through the geometric mean concentrations followsmooth exponential functions.

A cross inside a circle, indicate a suspected outlier, see 7.3. The suspected outliers aremerely indicated in the figures and are included in the statistical calculations except in afew cases, pointed out in the figures.

Each plot has a header with species name, age class and sampling locality. Age class maybe replaced bye shell length for blue mussels. Sampling locality is in a few cases in a codedform to save space; C1=herring, Harufjärden, C2=herring, Ängskärsklubb, C3=herring,Landsort, C4=herring, Utlängan, C6=herring, Fladen, V2=spring caught herring,Ängskärsklubb, V4=spring caught herring, Karlskrona archipelago, U8=guillemot egg, StKarlsö, G5=cod south east of Gotland, G6=cod, Fladen, P2=perch, Kvädöfjärden, M6=bluemussel, Fladen/Nidingen, M3=blue mussel, Väderöarna, L6=dab, Fladen, P3=flounder,Väderöarna. Below the header of each plot the results from several statistical calculationsare reported:

n(tot)= The first line reports the total number of analyses included together with thenumber of years ( n(yrs)= ).

m= The overall geometric mean value together with its 95% confidence interval is reportedon the second line of the plot (N.B. d.f.= n of years - 1).

slope= reports the slope, expressed as the yearly percentual change together with its 95%confidence interval.

sd(lr)= reports the square root of the residual variance around the regression line, as ameasure of between-year variation, together with the lowest detectable change in thecurrent time series with a power of 80%, one-sided test, =0.05. The last figure on this lineis the estimated number of years required to detect an annual change of 5% with a power of80%, one-sided test, =0.05.

power= reports the power to detect a log-linear trend in the time series (Nicholson &Fryer, 1991). The first figure represent the power to detect an annual change of 5% with thenumber of years in the current time series. The second figure is the power estimated as ifthe slope where 5% a year and the number of years were ten. The third figure is the lowestdetectable change (given in percent per year) for a ten year period with the current betweenyear variation at a power of 80%. The results of the power analyses from the various timeseries are summarised in chapter 9.

33

r2= reports the coefficient of determination (r2) together with a p-value for a two-sided test(H0: slope = 0) i.e. a significant value is interpreted as a true change, provided that theassumptions of the regression analysis is fulfilled.

y(96)= reports the concentration estimated from the regression line for the last yeartogether with a 95% confidence interval, e.g. y(96)=2.55(2.17,3.01) is the estimatedconcentration of year 1996 where the residual variance around the regression line is used tocalculate the confidence interval. Provided that the regression line is relevant to describe thetrend, the residual variance might be more appropriate than the within-year variance in thisrespect.

tao= reports Kendall's '', and the corresponding p-value.

sd(sm)= reports the square root of the residual variance around the smoothed line. Thesignificance of this line could be tested by means of an Analysis of Variance (see 7.1.3).The p-value is reported for this test. A significant result will indicate a non-linear trendcomponent.

Below these nine lines are additional lines with information concerning the regression ofthe last ten years.

In some few cases where an extreme outlying observation may hazard the confidence in theregression line, the ordinary regression line is replaced by the ‘Kendall-Theil Robust line’,see Helsel and Hirsch (1995) page 266. In these cases only the ‘Theil’-slope and Kendall’s‘‘ are reported.

7.5 Legend to the three dimensional maps

The height of the bars represents a geometric mean of the last 5 years or less if results arenot available

34

8 The power of the programme

Before starting to interpret the result from the statistical analyses of the time series it isessential to know with what power temporal changes can be detected (i.e. the chance toreveal true trends with the investigated matrices). It is crucial to know whether a negativeresult of a trend test indicate a stable situation or if the monitoring programme is too poor todetect even serious changes in the contaminant load to the environment. One approach tothis problem is to estimate the power of the time series based on the ‘random’ between-yearvariation. Alternatively the lowest detectable trend could be estimated at a fixed power torepresent the sensitiveness of the time series.

The first task would thus be to estimate the ‘random’ between-year variation. In the resultspresented below this variation is calculated using the residual distance from a log-linearregression line. In many cases the log-linear line, fitted to the current observations, seems tobe an acceptable ‘neutral’ representation of the true development of the time series. In caseswhere a significant ‘non-linear’ trend has been detected (see above), the regression line maynot serve this purpose; hence the sensitiveness- or power-results based on such time seriesare marked with an asterix in the tables below. These results are also excluded fromestimations of median performances.

Another problem is that a single outlier could ruin the estimation of the between-yearvariation. As an example, the time series of lead concentrations in fish liver seem to sufferfrom occasional outliers, especially in the beginning of the investigated period 1981-1984.The estimated median sensitiveness of these series is 12.5% a year. If a few outliers,identified by means of objective statistical criteria’s, are deleted, the calculated mediansensitiveness improves to 5.8%. In the presented results suspected outliers are includedwhich means that the power and sensitiveness might be underestimated.

Due to a change of method for metal analysis in 2004, values after 2003 are not presented.Metals will be analysed by a new laboratory from 2009 (material from 2007) and anintercalibration will be conducted to provide comparable results for the timeseries.

Table 8.1. reports the number of years that various contaminants have been analysed anddetected from the monitored sites. Generally the monitoring of trace metals has continuedfor about 25-30 years, PCB and DDT for about 25-30 years (spring caught herring andguillemot egg however, more than 35 years), HCH and HCB for about 20 years andPBDE/HBCD only for about 10 years.

35

Table 8.1. Number of years that various contaminants have been analysed and detected. C1=herring,Harufjärden, C2=herring, Ängskärsklubb, V2=spring caught herring, Ängskärsklubb, C3=herring, Landsort,C4=herring, Utlängan, V4=spring caught herring, Karlskrona archipelago, C6=herring, Fladen, C7=herring,Väderöarna, G5=cod south east of Gotland, G6=cod, Fladen, P1=perch, Holmöarna, P2=perch, Kvädöfjärden,Z1=eelpout, Holmöarna, Z2=eelpout, Kvädöfjärden, Z3, eelpout, Väderöarna, M2= blue mussel,Kvädöfjärden, M6=blue mussel, Fladen/Nidingen, M3=blue mussel, Väderöarna, L6=dab, Fladen,P3=flounder, Väderöarna, U8=guillemot egg, St Karlsö.

C1 C2 V2 C3 C4 V4 C6 C7 G5 G6 P1 P2 Z1 Z2 Z3 M2 M6 M3 L6 P3 U8

Hg** 26 26 15 27 27 14 27 11 28 28 12 24 11 12 12 11 24 26 14 15 34Pb* 21 22 8 23 23 5 23 9 23 23 9 8 7 9 8 9 21 22 14 14 8Cd* 22 22 8 23 23 7 23 9 23 23 9 9 7 9 8 9 21 22 14 14 8Ni* 9 9 8 9 9 7 9 9 9 9 8 8 7 9 8 9 9 9 - - 8Cr* 9 9 8 9 9 7 9 9 9 9 9 8 7 8 8 9 9 9 - - 8Cu* 22 22 8 23 23 7 23 9 23 23 9 8 7 9 8 9 21 22 14 14 8Zn* 21 21 8 22 22 7 22 9 22 22 9 8 7 9 8 9 21 21 13 13 8

sPCB 28 28 34 29 28 33 28 - 28 27 21 24 - - - - 21 22 13 15 36CB-153 19 19 19 21 20 19 20 12 19 18 14 20 11 13 13 13 20 19 5 6 20

DDE 28 28 34 29 28 33 28 12 27 27 22 25 11 13 13 13 22 22 14 15 36-HCH 11 16 16 21 20 18 14 7 19 18 5 14 6 8 4 13 14 14 6 6 17-HCH 10 17 19 21 20 19 10 2 19 11 4 3 6 11 2 11 9 5 - - 20-HCH 13 15 17 20 19 18 14 7 18 16 5 9 5 8 8 12 16 15 6 6 13HCB 19 18 19 20 20 19 20 11 19 18 14 16 11 13 13 13 9 10 6 6 21

TCDD-

eqv

17 - - - 18 - 18 - - - - - - - - - - - - - 37

BDE-47 9 9 6 9 9 5 9 8 9 9 - - - - - - - - - - 33HBCD 9 9 6 9 9 6 9 8 9 6 - - - - - - - - - - 34

values until 2003 ** values until 2006

Table 8.2 reports the number of years required to detect an annual change of 5% with apower of 80 %. The power is to a great extent dependent of the length of the time series andthe possibility to statistically verify an annual change of 5% at a power of 80% generallyrequires 15-20 years for the organic substances.

Table 8.2. Number of years required to detect an annual change of 5% with a power of 80 %. C1=herring,Harufjärden, C2=herring, Ängskärsklubb, C3=herring, Landsort, C4=herring, Utlängan, C6=herring, Fladen,V2=spring caught herring, Ängskärsklubb, V4=spring caught herring, Karlskrona archipelago, U8=guillemotegg, St Karlsö, G5=cod south east of Gotland, G6=cod, Fladen, P1=Holmöarna, P2=perch, Kvädöfjärden,M6=blue mussel, Fladen, M3=blue mussel, Väderöarna, L6=dab, Fladen, P3=flounder, Väderöarna.

MercuryBased on geometric means on a fresh weight basis

C1 C2 C3 C4 C6 U8 G5 G6 P2 M6 M3 Median

Hg** 16 25 *18 *19 15 *13 *14 *14 *18 *16 *19 16

Other trace metalsBased on geometric means on a dry weight basis

C1 C2 C3 C4 C6 G5 G6 M6 M3 P2 Median

Pb* 16 17 17 19 18 20 20 26 24 14 11

Cd* 19 17 *17 15 14 *16 *21 *13 *16 18 17

Cu* 15 12 *15 14 *15 16 20 13 *14 14 15

Zn* *13 11 11 *10 9 16 12 *14 *17 15 13

* values until 2003 ** values until 2006

36

OrganochlorinesBased on geometric means on a lipid weight basis

C1 C2 C3 C4 C6 C7 V2 V4 U8 G5 G6 P1 P2 M2 M6 M3 Median

sPCB 16 *15 *15 15 *14 - 18 *15 *12 17 22 *18 22 - *16 18 15.5DDE 21 *16 *17 *17 *18 17 19 *15 17 16 *17 *19 25 17 20 18 17

-HCH 10 14 11 8 7 8 9 *10 15 10 *13 8 16 17 13 18 12-HCH 10 *13 12 13 28 - 11 *14 *12 11 26 - - 16 23 17 13-HCH *11 16 12 *10 *16 22 11 *12 32 10 18 15 *19 14 *17 *18 15.5

HCB 14 20 19 19 15 18 18 16 *14 17 18 15 22 16 16 20 17TCDD-eqv 18 - - 16 18 - - - 14 - - - - - - - 17

BDE-47 19 15 16 *15 11 15 26 15 *22 *14 18 - - - - - 15HBCD 24 23 15 20 17 17 22 20 *18 *23 22 - - - - - 21

* indicates a significant non-linear trend component

In table 8.3 the lowest trend possible to detect within a 10-year period with a power of 80 %is presented both for the entire time series and for the latest 10-year period. The table showsthat the sensitiveness for Pb and Cd is approximately the same (10%-20%) whereas for Znand Cu it is somewhat better (5-10%). For PCB, DDE, HCH and HCB the estimatedsensitiveness is about 10-13%. For the TCDD-eqv the estimated median sensitiveness 12%.Biological variables like the condition index for herring, cod and perch show asensitiveness of about 1-2%.

Table 8.3. Lowest detectable trend within a 10-year period with a power of 80% for various variables invarious matrices at various sites. The top row for every substance gives the figure based on the residualvariance for the whole period, whereas the bottom row gives the figure for the last ten years of the time series.If no figure is given here this indicates that the time series show a significant non-linear trend component. Tocalculate power for these time series is not relevant.

MercuryBased on geometric means on a fresh weight basis

C1 C2 C3 C4 C6 G5 G6 P2 U8 M6 M3 Median

Hg** 10 24 - - 9.7 - - - - - 9.312 21 - - 9.8 - - - - - 12.5

Other trace metalsBased on geometric means on a dry weight basis

C1 C2 C3 C4 C6 G5 G6 M6 M3 Median

Pb* 11 12 11 15 14 16 15 24 22 1212 14 14 12 8.1 21 12 13 23 5.3

Cd* 15 12 - 9.9 8.6 - - - - 9.417 11 - 10 7.4 - - - - 10

Cu* 9.3 6.9 - 7.9 - 10 15 6.9 - 9.28.9 7.7 - 6.2 - 13 18 7.3 - 9.7

Zn* - 5.4 5.8 - 4.1 11 6.5 - - 7.25- 7.3 4.2 - 5.1 15 5.3 - - 8.85

* values until 2003 ** values until 2006

37

OrganochlorinesBased on geometric means on a lipid weight basis

C1 C2 V2 C3 C4 V4 C6 C7 G5 G6 P1 P2 U8 M2 M6 M3 Med

sPCB 11 9.5 13 9.9 9.3 9.4 8.6 - - - - 18 6.5 - - - 119.5 5.8 15 8.5 11 9.8 7.3 - - - - 18 7.0 - - - 10

DDE 17 11 15 12 11 9.9 13 12 10 - - - - 12 16 13 1314 10 17 8.1 11 11 15 14 12 - - - - - 12 8.0 12

-HCH 4.8 7.9 3.9 5.8 3.1 - 2.7 3.2 4.4 - 3.1 10 9.5 12 7.8 13 6.5-HCH 5.0 - 5.1 6.8 7.1 - 29 - 5.2 25 - - - 11 20 12 11-HCH - 10 5.6 6.5 - - - 19 4.9 13 9.4 - 35 8.2 - - 11

HCB 8.4 15 13 14 15 10 9.3 13 12 13 9.1 18 - 11 10 16 12TCDD-

eqv

13 - - - 11 - 13 - - - - - - - - - 12

BDE-47 15 9.6 24 11 - 9.5 5.3 9.2 - 13 - - - - - - 12HBCD 21 19 18 9.7 16 15 12 12 - 18 - - - - - - 16

Biological variablesC1 C2 V2 C3 C4 V4 C6 C7 G5 G6 P1 P2 Med

Cond 1.6 2.2 - 2.3 - 1.6 2.0 1.9 - - 1.6 1.2 1.71.2 0.9 - 1.4 - 2.0 1.7 1.9 - - 1.0 1.6 1.55

Fat 7.9 9.4 - - 10 - 10 14 - 18 2.4 - 9.95.6 5.7 - - 11 - 5.8 - - 9.9 2.5 - 6.65

Table 8.4 reports the power to detect an annual change of 5% covering the monitoringperiod, i.e. the length of the time series varies depending on site and investigatedcontaminant. For the long time series the estimated power is close to100% in most cases.For the shorter time series of HCH’s and HCB however, about 80-100%. For the series of- and -HCH though, the decreasing rate has been considerable (about 15-20% a year)leading to statistically significant results from most sites.

Table 8.4. Power to detect an annual change of 5% covering the entire monitoring period. The length of thetime series varies depending on site and investigated contaminant. In cases where considerable increasedpower has been achieved during the recent ten years period, this value has been used. * indicates a significantnon-linear trend.

MercuryBased on annual geometric mean concentrations on a fresh weight basis

C1 C2 C3 C4 C6 G5 G6 P2 U8 M6 M3

Hg 1.0 .85 *1.0 *1.0 1.0 *1.0 *1.0 *1.0 *1.0 *1.0 *1.0

Other trace metalsBased on annual geometric mean concentrations on a dry weight basis

C1 C2 C3 C4 C6 G5 G6 M6 M3

Pb .99 1.0 1.0 .97 .99 .96 .96 .55 .69Cd .95 .99 *1.0 *1.0 1.0 *1.0 *.93 *1.0 *1.0Cu 1.0 1.0 *1.0 1.0 *1.0 1.0 .96 *1.0 *1.0Zn *1.0 1.0 *1.0 *1.0 1.0 1.0 1.0 *1.0 *.99

38

OrganochlorinesBased on annual geometric mean concentrations on a lipid weight basis

C1 C2 V2 C3 C4 V4 C6 C7 G5 G6 P1 P2 U8 M2 M6 M3

sPCB 1.0 1.0 1.0 1.0 1.0 1.0 1.0 - *1.0 *.99 *.97 .93 1.0 - *1.0 *.98DDE 1.0 1.0 1.0 1.0 1.0 1.0 1.0 .36 1.0 *1.0 *.97 *.84 *1.0 1.0 .92 .98

-HCH .93 .97 1.0 1.0 1.0 *1.0 1.0 .68 1.0 *1.0 .24 .67 .94 1.0 .89 .46-HCH .81 *.99 1.0 1.0 1.0 *1.0 .08 - 1.0 .11 - - *1.0 .35 .09 .07-HCH *.97 .78 *1.0 1.0 *1.0 *1.0 *.63 .07 1.0 .65 .07 *.13 .10 .65 *.77 *.60

HCB 1.0 .70 .92 *.90 *.88 .98 1.0 .25 .95 .84 .79 .42 *1.0 .55 .21 .14TCDD-eqv .76 - - - .95 - .85 - - - - - *1.0 - - -

BDE-47 .13 .23 .06 .19 *.24 .07 .59 .18 *.27 .14 - - *.10 - - -HBCD .09 .10 .06 .23 .12 .07 .17 .13 *.10 .06 - - *1.0 - - -

39

9 ConditionUpdated 09.05.31

The stoutness of fish, i.e. weight against length is a common measure of the ‘degree ofwell-being’ of an individual or a population.

In this report the commonly used ‘condition factor’, K, (Vibert & Lagler, 1961) is used:

K = 100 W / L3

where the weight (W) is given in grams and the length (L) in centimetres.

9.1 Temporal variation

Significant decreasing trends for the condition factor of herring are observed fromHarufjärden, Landsort and Utlängan (autumn and spring) while it increases atÄngskärsklubb in spring caught herring for the whole time series and in autumn caughtherring during the last ten years. The increase at Ängskärsklubb may be explained by anunintentional increase of the average age over time in the collected samples.

The condition factor estimated for cod show significant upward trends at both Gotland andFladen over the whole investigated period, but for the recent 5-10 years indications of adecreasing trend is observed at both locations. The observed increase might be explained bythe simultaneous decrease in population density during the investigated period.

Significantly decreasing trends for the condition factor are observed at Holmöarna for perchand eelpout.

9.2 Spatial variation

The average condition factor, estimated over a period of over 20 years is slightly lower inherring sampled at Harufjärden in the northern parts of the Bothnian Bay compared tosamples from Fladen and Väderöarna at the Swedish west coast.

40

Condition factor, herringHarufjarden (3-4)

.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

80 85 90 95 00 05

n(tot)=492,n(yrs)=28m=.632 (.617,.647)slope=-.49%(-.70,-.29)SD(lr)=9.8,.40%,6 yrpower=1.0/1.0/1.6%y(07)=.590 (.571,.610)r2=.48, p<.001 *tao=-.50, p<.001 *SD(sm)=9.1, NS,1.5%slope=-.87%(-1.7,-.02)SD(lr)=6.6,1.2%,5 yrpower=1.0/1.0/1.2%r2=.41, p<.044 *

Angskarsklubb (3-5)

.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

80 85 90 95 00 05

n(tot)=498,n(yrs)=28m=.675 (.659,.691)slope=-.14%(-.42,.13)SD(lr)=15,.50%,7 yrpower=1.0/1.0/2.2%y(07)=.662 (.633,.692)r2=.04, NStao=-.03, NSSD(sm)=18, NS,2.6%slope=.86%(.27,1.5)SD(lr)=5.8,.90%,5 yrpower=1.0/1.0/.90%r2=.58, p<.010 *

Landsort (3-5)

.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

80 85 90 95 00 05

n(tot)=486,n(yrs)=29m=.648 (.630,.667)slope=-.44%(-.73,-.15)SD(lr)=15,.50%,7 yrpower=1.0/1.0/2.3%y(07)=.609 (.581,.639)r2=.27, p<.004 *tao=-.39, p<.003 *SD(sm)=12, p<.060,2.0%slope=.10%(-.91,1.1)SD(lr)=8.6,1.4%,6 yrpower=1.0/1.0/1.4%r2=.01, NS

Utlangan (2-4)

.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

80 85 90 95 00 05

n(tot)=600,n(yrs)=28m=.655 (.635,.676)slope=-.79%(-1.0,-.56)SD(lr)=12,.40%,6 yrpower=1.0/1.0/1.8%y(07)=.589 (.568,.611)r2=.65, p<.001 *tao=-.58, p<.001 *SD(sm)=9.0, p<.020,1.4%slope=-.13%(-.97,.71)SD(lr)=6.9,1.2%,5 yrpower=1.0/1.0/1.2%r2=.02, NS

pia - 09.04.16 15:21, CONDC

Condition factor, herringAngskarskl.(2-4), spring

n(tot)=581,n(yrs)=31

.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

75 85 95 05

m=.629 (.610,.650)slope=.40%(.13,.66)SD(lr)=17,.50%,8 yrpower=1.0/1.0/2.8%y(07)=.676 (.640,.715)r2=.24, p<.005 *tao=.30, p<.017 *SD(sm)=10, p<.001,1.7%slope=-.59%(-1.6,.38)SD(lr)=7.6,1.8%,5 yrpower=1.0/1.0/1.2%r2=.27, NS

Karlskrona (2-3), spring


.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

75 85 95 05

m=.654 (.642,.665)slope=-.19%(-.34,-.04)SD(lr)=11,.30%,6 yrpower=1.0/1.0/1.6%y(07)=.633 (.614,.652)r2=.18, p<.014 *tao=-.38, p<.002 *SD(sm)=12, NS,1.9%slope=-.84%(-2.2,.57)SD(lr)=13,2.0%,7 yrpower=1.0/1.0/2.0%r2=.19, NS

Fladen (2-3)


.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

80 85 90 95 00 05

m=.707 (.691,.723)slope=-.19%(-.47,.08)SD(lr)=16,.40%,7 yrpower=1.0/1.0/2.0%y(07)=.688 (.660,.718)r2=.08, NStao=-.14, NSSD(sm)=17, NS,2.1%slope=.19%(-1.0,1.4)SD(lr)=13,1.7%,6 yrpower=1.0/1.0/1.7%r2=.02, NS

Vaderoarna


.4

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

94 96 98 00 02 04 06 08

m=.738 (.714,.762)slope=.26%(-.69,1.2)SD(lr)=17,1.4%,6 yrpower=1.0/1.0/1.9%y(07)=.750 (.699,.804)r2=.04, NStao=.24, NSSD(sm)=17, NS,1.9%

pia - 09.04.16 15:23, CONDV

41

Condition factor, cod and perchCod (3-4), SE Gotland

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

80 85 90 95 00 05

n(tot)=429,n(yrs)=29m=1.01 (.978,1.04)slope=.42%(.08,.77)SD(lr)=838,.50%,8 yrpower=1.0/1.0/2.8%y(07)=1.07 (1.01,1.13)r2=.19, p<.018 *tao=.28, p<.036 *SD(sm)=524, p<.001,1.7%slope=-.25%(-1.9,1.4)SD(lr)=604,2.3%,7 yrpower=1.0/1.0/2.3%r2=.02, NS

Cod (2-3), Fladen

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

80 85 90 95 00 05

n(tot)=479,n(yrs)=29m=.985 (.957,1.01)slope=.44%(.13,.74)SD(lr)=440,.50%,7 yrpower=1.0/1.0/2.4%y(07)=1.05 (1.00,1.10)r2=.24, p<.007 *tao=.24, p<.072SD(sm)=333, p<.011,1.8%slope=-.32%(-1.2,.61)SD(lr)=1759,1.3%,6 yrpower=1.0/1.0/1.3%r2=.07, NS

Perch, Holmoarna

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

2.1

2.2

2.3

2.4

80 85 90 95 00 05

n(tot)=306,n(yrs)=23m=1.20 (1.17,1.22)slope=-.27%(-.49,-.05)SD(lr)=25,.50%,6 yrpower=1.0/1.0/1.6%y(07)=1.15 (1.12,1.20)r2=.23, p<.019 *tao=-.30, p<.042 *SD(sm)=24, NS,1.6%slope=-.13%(-.84,.57)SD(lr)=17,1.0%,5 yrpower=1.0/1.0/1.0%r2=.02, NS

Kvadofjarden (3-4)

.5

.6

.7

.8

.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

2.1

2.2

2.3

2.4

80 85 90 95 00 05

n(tot)=298,n(yrs)=27m=1.21 (1.19,1.23)slope=.12%(-.05,.28)SD(lr)=18,.30%,5 yrpower=1.0/1.0/1.2%y(07)=1.23 (1.20,1.26)r2=.08, NStao=.25, p<.070SD(sm)=18, NS,1.2%slope=.81%(-.35,2.0)SD(lr)=23,1.9%,6 yrpower=1.0/1.0/1.6%r2=.28, NS

pia - 09.04.16 15:25, CONDGP

Condition factor, eelpoutHolmoarna


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

1.0

1.1

94 96 98 00 02 04 06 08

m=.325 (.312,.338)slope=-1.1%(-2.0,-.24)SD(lr)=4.4,1.3%,6 yrpower=1.0/1.0/1.8%y(07)=.305 (.288,.324)r2=.44, p<.018 *tao=-.39, p<.075SD(sm)=3.7, NS,1.5%slope=-.42%(-1.5,.65)SD(lr)=3.7,1.5%,6 yrpower=1.0/1.0/1.5%r2=.09, NS

Kvadofjarden


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

1.0

1.1

94 96 98 00 02 04 06 08

m=.371 (.360,.383)slope=.18%(-.70,1.1)SD(lr)=5.4,1.3%,6 yrpower=1.0/1.0/1.9%y(07)=.375 (.353,.399)r2=.02, NStao=.03, NSSD(sm)=5.7, NS,2.0%slope=.30%(-1.2,1.8)SD(lr)=5.8,2.1%,7 yrpower=1.0/1.0/2.1%r2=.03, NS

Vaderoarna


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

1.0

1.1

90 95 00 05

m=.433 (.409,.458)slope=-.50%(-1.6,.56)SD(lr)=13,1.8%,9 yrpower=1.0/.96/3.8%y(07)=.416 (.376,.461)r2=.07, NStao=-.27, NSSD(sm)=13, NS,3.8%slope=-.40%(-3.0,2.1)SD(lr)=12,3.6%,9 yrpower=.98/.98/3.6%r2=.02, NS

pia - 09.04.16 15:37, CONDZ

42

10 Fat contentUpdated 09.05.31

The fat content is determined in samples that are analysed for organochlorines i.e. herring,eelpout (dab and flounder) muscle, cod liver and blue mussel soft body. A strong negativecorrelation between concentrations of organochlorines (expressed on a fat weight basis) andfat content in spring caught herring has been shown (Bignert et al. 1993) but also betweenthe concentration of various metals and fat content in cod liver (Grimås et al. 1985). Theanalysed concentrations of these contaminants are hence adjusted for varying fat content.

In general, an extremely low fat content, due to e.g. starvation, may cause elevatedconcentrations of organo chlorines expressed on a fat weight basis.

The sample fat content is determined after extraction with acetone and hexane with 10%ether without heating (Jensen et al. 1983) in the present investigation.

The result of the fat determination may vary considerable depending on the extractionmethod used.

In herring muscle tissue, the subcutaneous fat layer is removed before the samples areprepared. Analyses of fat content including skin and subcutaneous fat shows at least 1.5times higher fat content.


In the Baltic, decreasing trends of fat in herring muscle tissue are indicated fromHarufjärden, Landsort and Utlängan (autumn and spring). The fast decrease at Landsort andUtlängan (autumn) seems to have ceased during the past decade (with an exception of lasttwo years when the fat content was down to really low levels, less than 2%).

Overall increasing trends in fat content are found in cod liver from south east of Gotlandand Fladen, but during the past ten years the fat content has decreased in cod liver southeast of Gotland. The fluctuating fat content in cod has to be considered when evaluating thetime series of trace metals in cod liver (see above).

Decreasing trends of fat content in perch muscle are indicated at both Holmöarna andKvädöfjärden in the Baltic. Eelpout from Holmöarna in the Baltic proper and Väderöarnaon the west coast is also showing a decline in fat content.

The time series of blue mussel from Väderöarna shows a decrease in fat content during thepast ten years.


Today, the fat content in autumn caught herring from the Baltic is rather similar in muscletissue from all investigated sites. In the beginning of the eighties however, the samples fromÄngskärsklubb in the Bothnian Sea and Harufjärden in the Bothnian Bay were lowercompared to samples from the Baltic Proper.

43

The fat content in herring from Skagerack varies and can sometimes be about twice as highcompared to herring muscle from the Baltic and the Kattegatt. This is not surprising sinceAtlantic herring muscle tissue may contain more than 15% fat.

The fat content in cod liver is highly variable even between specimens caught at the sametime at the same place. The geometric mean fat content over time in samples from SE ofGotland is more than 2.5 times higher compared to cod livers from the Kattegatt. Thisdifference is significant.

10.3 Seasonal variation

Fat content in spring caught herring from Ängskärsklubb show approximately the samemean value as herring from the same site caught in the autumn whereas herring fromKarlskrona archipelago caught in the autumn show about 30% higher mean fat contentcompared to spring caught herring from the same area.

44

Table 10.1. Geometric mean fat content (%) in various matrices with a 95% confidence interval. Totalnumber of analysed individual specimens and number years are also reported. Last years values are estimatedfrom trend if p<0.1 or from the mean if no trend is present.

* significant trend, p < 0.05

Matrix age n Nyrs

Year trend (95% ci) last year (95% ci)

Herring muscleHarufj. autumn 3-4 579 28 78-07 -1.5 (-2.5,-.55)* 2.2 (1.9-2.6)Ängskärskl. aut. 3-5 478 28 78-07 2.3 (1.9-2.8)

” spring 2-5 624 34 72-07 2.7 (2.3-3.3)Landsort 3-5 451 29 78-07 -1.7 (-3.1,-.22)* 2.8 (2.2-3.5)Utlängan, aut. 2-4 583 28 80-07 -3.7(-5.0, -2.4)* 1.8 (1.5-2.3)

” spring 2-3 577 33 72-07 -2.0 (-2.9, -1.1)* 1.5 (1.3-1.8)Fladen 2-3 623 28 80-07 3.9 (3.1-4.8)Väderöarna 249 12 95-07 4.9 (2.9-8.1)

Cod liverSE Gotland 3-4 407 28 80-07 2.1 (1.3, 3.0)* 70 (61-81)Fladen 2-3 450 28 80-07 2.3 (.03, 4.6)* 25 (18-36)

Perch muscleHolmöarna 283 22 80-07 -.91 (-1.2,-0.58)* .67 (.63-.70)Kvädöfjärden 302 26 80-07 -.97 (-1.5,-0.45)* .62 (.57-.67)

Eelpout muscleHolmöarna 97 11 95-07 -4.7 (-8.2, -1.3)* .55 (.44-.70)Kvädöfjärden 121 13 95-07 .61 (.50-.74Väderöarna 236 16 88-07 -3.1 (-6.2,.02)* .55 (.41-.74)

Dab muscleFladen 3-6 158 13 81-94 -3.7 (-5.2,-2.2)* .61 (.54-.68)

Flounder muscleVäderöarna 4-6 190 15 80-94 -3.4 (-5.7, -1.0)* .60 (.50-.73)

Blue musselFladen 85 25 81-07 .89 (.60-1.3)Väderöarna 92 27 80-07 1.5 (1.1-2.0)Kvädöfjärden 61 13 95-07 1.4 (1.0-1.8)

Guillemot eggSt. Karlsö 391 37 69-07 12 (11-13)

45

Fat %, herring muscle

Harufjarden (3-4)

0

2

4

6

8

10

12

14

80 85 90 95 00 05

0

2

4

6

8

10

12

14

n(tot)=579,n(yrs)=28m=2.77 (2.52,3.06)slope=-1.5%(-2.5,-.55)SD(lr)=21,1.5%,14 yrpower=1.0/.43/7.9%y(07)=2.24 (1.91,2.63)r2=.28, p<.004 *tao=-.43, p<.001 *SD(sm)=26, NS,9.6%slope=-2.1%(-6.0,1.9)SD(lr)=18,5.6%,11 yrpower=.72/.72/5.6%r2=.16, NS

Angskarsklubb (3-5)

0

2

4

6

8

10

12

14

80 85 90 95 00 05

0

2

4

6

8

10

12

14

n(tot)=478,n(yrs)=28m=2.52 (2.28,2.79)slope=-.62%(-1.8,.55)SD(lr)=28,1.8%,15 yrpower=1.0/.32/9.4%y(07)=2.32 (1.92,2.80)r2=.04, NStao=-.15, NSSD(sm)=30, NS,10%slope=2.8%(-1.2,6.8)SD(lr)=19,5.7%,11 yrpower=.70/.70/5.7%r2=.24, NS

Landsort (3-5)

0

2

4

6

8

10

12

14

80 85 90 95 00 05

0

2

4

6

8

10

12

14

n(tot)=451,n(yrs)=29m=3.49 (3.06,3.99)slope=-1.7%(-3.1,-.22)SD(lr)=26,2.1%,17 yrpower=1.0/.22/12%y(07)=2.76 (2.17,3.50)r2=.17, p<.024 *tao=-.24, p<.072SD(sm)=21, p<.044,9.8%slope=1.6%(-4.2,7.4)SD(lr)=19,8.3%,14 yrpower=.39/.39/8.3%r2=.05, NS

Utlangan (2-4)

0

2

4

6

8

10

12

14

80 85 90 95 00 05

0

2

4

6

8

10

12

14

n(tot)=583,n(yrs)=28m=3.03 (2.58,3.55)slope=-3.7%(-5.0,-2.4)SD(lr)=25,1.9%,16 yrpower=1.0/.28/10%y(07)=1.84 (1.49,2.27)r2=.55, p<.001 *tao=-.56, p<.001 *SD(sm)=24, NS,9.7%slope=-.77%(-8.2,6.7)SD(lr)=37,11%,16 yrpower=.26/.26/11%r2=.01, NS

pia - 09.04.16 16:24, FATC

Fat %, herring muscleAngskarsklubb(2-5), spring


0

2

4

6

8

10

12

14

75 85 95 05

0

2

4

6

8

10

12

14

m=2.58 (2.36,2.83)slope=.32%(-.55,1.2)SD(lr)=28,1.4%,15 yrpower=1.0/.31/9.7%y(07)=2.73 (2.29,3.25)r2=.02, NStao=.13, NSSD(sm)=20, p<.004,7.0%slope=3.0%(-3.2,9.3)SD(lr)=30,9.0%,15 yrpower=.35/.35/9.0%r2=.14, NS

Karlskrona (2-3), spring


0

2

4

6

8

10

12

14

75 85 95 05

0

2

4

6

8

10

12

14

m=2.10 (1.87,2.36)slope=-2.0%(-2.9,-1.1)SD(lr)=35,1.4%,15 yrpower=1.0/.32/9.4%y(07)=1.50 (1.26,1.78)r2=.41, p<.001 *tao=-.45, p<.001 *SD(sm)=29, p<.046,7.9%slope=-.04%(-4.1,4.0)SD(lr)=31,5.8%,11 yrpower=.68/.68/5.8%r2=.00, NS

Fladen (2-3)


0

2

4

6

8

10

12

14

80 85 90 95 00 05

0

2

4

6

8

10

12

14

m=4.15 (3.72,4.62)slope=-.49%(-1.8,.86)SD(lr)=20,2.0%,16 yrpower=1.0/.28/10%y(07)=3.88 (3.14,4.80)r2=.02, NStao=-.04, NSSD(sm)=19, NS,10%slope=3.9%(-.19,7.9)SD(lr)=11,5.8%,11 yrpower=.69/.69/5.8%r2=.38, p<.058

Vaderoarna


0

2

4

6

8

10

12

14

90 95 00 05

0

2

4

6

8

10

12

14

m=5.13 (4.07,6.48)slope=-.82%(-7.7,6.0)SD(lr)=23,10%,19 yrpower=.27/.17/14%y(07)=4.87 (2.94,8.07)r2=.01, NStao=-.06, NSSD(sm)=20, NS,12%

pia - 09.04.27 10:46, FATV

46

Fat %, cod liver and perch muscle

Perch

Cod (3-4), SE Gotland

0

20

40

60

80

100

120

80 85 90 95 00 05

0

20

40

60

80

100

120

n(tot)=407,n(yrs)=28m=53.1 (48.1,58.6)slope=2.1%(1.2,3.0)SD(lr)=4.8,1.3%,13 yrpower=1.0/.52/7.0%y(07)=70.3 (60.8,81.4)r2=.45, p<.001 *tao=.43, p<.001 *SD(sm)=3.1, p<.001,4.5%slope=-1.7%(-4.5,1.1)SD(lr)=2.7,4.0%,9 yrpower=.94/.94/4.0%r2=.19, NS

Cod (2-3), Fladen

0

20

40

60

80

100

120

80 85 90 95 00 05

0

20

40

60

80

100

120

n(tot)=450,n(yrs)=28m=18.5 (15.2,22.4)slope=2.3%(.03,4.6)SD(lr)=16,3.3%,22 yrpower=.99/.13/18%y(07)=25.2 (17.6,36.0)r2=.14, p<.045 *tao=.18, NSSD(sm)=15, NS,17%slope=2.1%(-4.7,9.0)SD(lr)=8.9,9.9%,15 yrpower=.30/.30/9.9%r2=.06, NS

Holmoarna

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2

80 85 90 95 00 05

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2 n(tot)=283,n(yrs)=22m=.751 (.717,.787)slope=-.91%(-1.2,-.58)SD(lr)=23,.70%,7 yrpower=1.0/1.0/2.4%y(07)=.668 (.634,.704)r2=.62, p<.001 *tao=-.55, p<.001 *SD(sm)=24, NS,2.5%slope=-.21%(-2.0,1.6)SD(lr)=19,2.5%,7 yrpower=1.0/1.0/2.5%r2=.01, NS

Kvadofjarden

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2

80 85 90 95 00 05

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2 n(tot)=302,n(yrs)=26m=.705 (.669,.743)slope=-.97%(-1.5,-.45)SD(lr)=30,.80%,9 yrpower=1.0/.97/3.7%y(07)=.619 (.570,.671)r2=.38, p<.001 *tao=-.43, p<.002 *SD(sm)=22, p<.016,2.8%slope=-.21%(-2.4,2.0)SD(lr)=18,3.6%,8 yrpower=.98/1.0/3.0%r2=.01, NS

pia - 09.04.27 10:50, FATGP

Fat %, blue mussel soft bodyFladen

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

80 85 90 95 00 05

n(tot)=85,n(yrs)=25m=1.08 (.871,1.34)slope=-1.5%(-4.3,1.2)SD(lr)=681,4.3%,23 yrpower=.92/.11/20%y(07)= .89 ( .60,1.33)r2=.05, NStao=-.17, NSSD(sm)=365, p<.001,10%slope=-1.8%(-6.3,2.6)SD(lr)=94,6.3%,12 yrpower=.60/.60/6.3%r2=.10, NS

Vaderoarna

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

80 85 90 95 00 05

n(tot)=92,n(yrs)=27m=1.33 (1.14,1.55)slope=.96%(-.93,2.8)SD(lr)=139,2.9%,19 yrpower=1.0/.16/15%y(07)=1.51 (1.12,2.03)r2=.04, NStao=.13, NSSD(sm)=99, p<.006,10%slope=-6.1%(-11,-.82)SD(lr)=49,7.5%,13 yrpower=.46/.46/7.5%r2=.47, p<.028 *

Kvadofjarden

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

94 96 98 00 02 04 06

n(tot)=61,n(yrs)=13m=1.27 (1.09,1.47)slope=1.1%(-3.0,5.2)SD(lr)=106,5.9%,15 yrpower=.67/.33/9.2%y(07)=1.35 (1.01,1.80)r2=.03, NStao=.08, NSSD(sm)=94, NS,8.0%slope=-2.5%(-7.3,2.3)SD(lr)=65,6.8%,12 yrpower=.54/.54/6.8%r2=.15, NS

pia - 09.04.29 16:54, FATM

47

Fat %, Eelpout

Holmoarna

n(tot)=97,n(yrs)=11

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2

94 96 98 00 02 04 06

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2m=.722 (.608,.858)slope=-4.7%(-8.2,-1.3)SD(lr)=58,5.8%,12 yrpower=.69/.54/6.8%y(07)=.551 (.436,.697)r2=.52, p<.012 *tao=-.31, NSSD(sm)=51, NS,6.0%

Kvadofjarden


.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2

94 96 98 00 02 04 06

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2m=.593 (.536,.655)slope=.48%(-2.3,3.3)SD(lr)=33,4.0%,12 yrpower=.95/.62/6.2%y(07)=.610 (.500,.744)r2=.01, NStao=.13, NSSD(sm)=20, p<.010,3.8%

Vaderoarna


.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2

90 95 00 05

.0

.4

.8

1.2

1.6

2.0

2.4

2.8

3.2m=.705 (.586,.848)slope=-3.1%(-6.2,.02)SD(lr)=89,5.2%,17 yrpower=.78/.23/12%y(07)=.551 (.409,.743)r2=.24, p<.049 *tao=-.32, p<.087SD(sm)=98, NS,13%

pia - 09.04.27 10:53, FATZ

Fat %, guillemot egg, early laid


0

4

8

12

16

20

24

28

32

36

70 75 80 85 90 95 00 05

0

4

8

12

16

20

24

28

32

36

m=12.1 (11.7,12.6)slope=-.04%(-.36,.28)SD(lr)=4.25,.50%,9 yrpower=1.0/.96/3.8%y(07)=12.0 (11.2,12.9)r2=.00, NStao=-.02, NSSD(sm)=3.59, p<.042,3.2%slope=.43%(-.78,1.6)SD(lr)=1.91,1.7%,6 yrpower=1.0/1.0/1.7%r2=.08, NS

pia - 08.03.13 10:17, FATU

48

11 MercuryUpdated 08.03.28

Due to a change of laboratory for metal analysis in 2008, values after 2006 are notpresented in this section.

Mercury is one of the mandatory contaminants that should be analysed and reported withinboth the OSPARCOM and HELCOM conventions.

The concentration of mercury in fish muscle and blue mussel soft body is determined usinga ‘Mercury Monitor LCD 3200’ detector at the Department of Environmental Assessment atSwedish University of Agricultural Sciences. The detection limit is estimated toapproximately 10 ng/g dry weight.

Table 11.1. Mean divergence from standard value of analysed CRM (Certified Reference Material). The lastcolumn shows the mean deviation from the standard, including the sign.

Year CRM n % %

94 DORM-2 16 4.6 -0.295 DORM-2 38 3.6 -0.696 DORM-2 20 3.9 2.697 DORM-2 4 5.0 -0.3

The uncertainty of a single analytical value is estimated to be between 3-5% in average. Thedeviation of the mean value (including the sign) of the analysed CRM samples, from thestandard value is less than 3%.

In 1992, new analytical equipment was introduced and great efforts have been made tointercallibrate the new method by reanalysing old samples both dried extracts and samplesfrom the Environmental Specimen Bank.


11.1.1 Conventions, aims and restrictions

The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the mercury discharges are to be reduced by 70% between 1985 and1995, using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of thedischarges of mercury to air and water by 50% by 1995 with 1987 as a base year.

The use of mercury in the paper pulp industries has been banned in Sweden since 1966.

According to a governmental proposition (1993/94:163) the aim is that all mercury usageshould have ceased the year 2000 in Sweden.

49

11.1.2 This investigation

There is no common general trend for mercury in herring muscle for the investigated timeseries. The time series from Landsort show a significant increasing trend of about 2% peryear for the whole time period, but during the last ten years the concentrations havedecreased. Mercury was monitored in spring caught herring from Ängskärsklubb andKarlskrona for four years in the beginning of the seventies, and these series were continuedin 1996. Both series show a significant decrease. Both time series from the Swedish westcoast (Fladen and Väderöarna) show a significant increase of between 1 and 6%

The time series from Ängskärsklubb in the Bothnian Sea shows a very large between-yearvariation. Although the sampling site at Ängskärsklubb is located rather far off the coast,the mercury concentration in the herring samples could be influenced by local discharges.Ängskärsklubb may thus not be representative of the Bothnian Sea. During 1995-1996 theestimated mean concentration in herring muscle from Ängskärsklubb were on the samelevel as measured in comparable samples from Landsort. However, in 1997 and 1999 thegeometric mean concentrations increased to the same level that was recorded in thebeginning of the eighties.

The number of years required to detect an annual change of 5% varied between 13 to 19 (25for Ängskärsklubb) years for the herring time series. The power to detect a 5% annualchange is close to 100% for most of the long herring and cod series. The large between-yearvariation in Ängskärsklubb lowers the power of that specific time series to about 85%.

Perch muscle samples from Kvädöfjärden in the Baltic Proper show a significant decreasingtrend.

Cod from SE of Gotland show a significant increasing linear trend.

Mercury concentration in eelpout showed a significant increasing trend at Väderöarna.

The mercury concentration in blue mussels from Kvädöfjärden in the Baltic Proper hasincreased significantly during the last ten years. A similar pattern can also be seen in bluemussels from Väderöarna and Fladen on the Swedish west coast.

Guillemot eggs from St Karlsö in the Baltic proper show a significant decreasing trend ofabout 1.5% a year in mercury concentration. It should be noted that the mercury analyses inthis time series have been carried out in a retrospective study i.e. all analyses have beenperformed at one occasion at the same laboratory.

11.1.3 Conclusion

The results concerning the development of mercury concentration in the investigatedmatrices are not consistent. The mercury concentration in guillemot egg decreases whereasthe concentration in herring from the northern Baltic Proper seems to increase or fluctuate.The future development of mercury has to be studied carefully and possible analyticalproblems thoroughly investigated.

50


0 - 50

50 - 100

ng/g ww

TISS - 08.03.27 11:09, Hg3leg

Figure 11.1. Spatial variation in concentration (w.w.) of mercury in herring liver.

Herring muscle from Ängskärsklubb show the highest mercury concentrations of all herringsamples. This might be due to local discharges. Samples collected during the eighties fromÄngskärsklubb are thus most probably not representative of the Bothnian Sea, regarding themercury concentration. In the beginning of the eighties the mercury concentrations inherring from Ängskärsklubb ranged from 60-180 ng/g. Finnish mercury analyses of herringmuscle samples between 1980-83 from the eastern part of the Bothnian Sea showconcentrations around 20 ng/g (ICES, 1995), i.e. the same level as the results fromÄngskärsklubb in 1994-1996.

Among the other herring sites, Harufjärden show the highest mercury concentration overtime, significantly higher than Landsort, Utlängan and Fladen. The time series fromUtlängan in the southern Baltic proper shows the lowest mercury concentrations in theBaltic with a geometric mean concentration about 17 ng/ g.

Cod muscle tissue from Fladen in the Kattegatt (56 ng/g) show significantly higherconcentrations than samples from south east of Gotland (40 ng/g). Finnish data of mercuryin cod from the Bothnian Sea and from the mouth of the Gulf of Finland showconcentrations in the same range as the Swedish data from Gotland (ICES, 1995). Themercury concentration in cod muscle from Fladen is however within the same range as incod muscle from the same age class from reference stations along the Norwegian coast(Green & Rönningen, 1994) analysed at NIVA.

51

Perch muscle samples from Holmöarna in the Quark show significantly higherconcentrations (64 ng/g) compared to perch samples from Kvädöfjärden (24 ng/g) at thecoast of the Baltic Proper. The estimated geometric mean concentration for Holmöarna2006 is about 3 times higher than for Kvädöfjärden 2006.

The mercury concentration in flounder from the Skagerack show values in the same rangeas Danish flounder samples from the Belt Sea but significantly lower compared to Danishflounder samples from the Sound (ICES, 1995).

Mercury in blue mussels from Fladen in Kattegatt and Väderöarna in Skagerack show nospatial variation. The overall mean concentration in blue mussel samples from the two sites,exceed the upper limit of the range of ‘present background concentrations in pristine areaswithin the OSPAR Convention Area’ proposed to be between 5-10 ng/g wet weight (ICES,1997).

The estimated mean concentrations for 2006 in herring and cod muscle (accept for cod fromFladen (56 ng/g), perch and eelpout from Holmöarna (64 and 72 ng/g respectively) andeelpout from Kvädöfjärden (76 ng/g)); all fall inside the range proposed as the ‘presentbackground concentrations in pristine areas within the OSPAR Convention Area’ (10-50ng/g fresh weight in round fish, ICES, 1997).


No significant differences in mercury concentrations were found between spring andautumn caught herring from Ängskärsklubb and Karlskrona.

11.4 Species differences

Significant differences in mean mercury concentration (ng/g w.w.), in fish muscle and bluemussel soft body, were found between various species at the Swedish west coast.

Holmöarna: Eelpout(82) > Perch(65)Kvädöfjärden: Eelpout(77) > Blue mussel(25) - Perch(24)Fladen: Cod(53) > Herring(30) > Blue mussel(14)Väderöarna: Eelpout(44) - Herring(34) - > Blue mussel(15)

The mercury concentration in blue mussel is in general lower than in fish muscle. Thelevels found in guillemot eggs are 3 to 20 times higher compared to the levels in fishmuscle.

The concentration in fish muscle from the various sites all fall below the suggested limit (bythe Swedish National Food Administration – SNFA) for human consumption (500 ng/gfresh weight) by a factor 6-25. However, the suggested limit for children’s food is 50 ng/g,which is close to the overall mean concentration in fish muscle from most of theinvestigated sites (SLVFS, 1993). The limit within the European Community for severalfish species is set to 500 ng/g fresh weight (EG, 2001).

52

Table 11.2. Estimated geometric mean concentrations of mercury (ng/g fresh weight) for the last sampledyear in various matrices and sites during the investigated time period. The trend is reported, if p<0.1. The ageinterval for fish, and the length interval for blue mussels are also presented together with the total number ofanalyses and the number of years of the various time-series.

Matrix age n nyrs

year trend (95% ci) last year (95% ci)

Herring muscleHarufj. autumn 3-4 412 26 80-06 39 (35-43)Ängskärskl. aut. 3-5 427 26 80-06 55 (43-70)

” spring 210 15 72-75,96-06 -2.8 (-3.9,-1.7)* 24 (19-29)Landsort 3-5 406 27 80-06 1.6 (-.12, 3.3) 35 (27-46)Utlängan, aut. 2-4 424 27 80-06 17 (15-20)

” spring 176 14 72-75,96-06 -1.0 (-1.9,-0.15)* 18 (15-21)Fladen 2-3 489 27 80-06 1.4 (0.05, 2.7)* 30 (25-37)Väderöarna 220 11 95-05 5.6 (1.1, 10)* 34 (26-44)

Cod muscleSE Gotland 3-4 402 28 79-06 2.2 (1.1, 3.3)* 40 (34-48)Fladen 2-3 447 28 79-06 53 (49-58)

Perch muscleHolmöarna 3-6 134 12 91,95-06 65 (55-76)Kvädöfjärden 3-6 236 24 81-06 -3.3 (-5.2, -1.4)* 24 (18-32)

Eelpout muscleHolmöarna 107 11 95-06 82 (70-96)Kvädöfjärden 119 12 95-06 77 (65-91)Väderöarna 120 12 95-06 10 (3.1, 17)* 44 (28-68)

Dab muscleFladen 3-6 278 14 81-94 78 (52-115)

Flounder muscleVäderöarna 4-6 248 14 81-94 46 (25-83)

Blue mussel shell lFladen 473 24 81-06 14 (13-16)Väderöarna 499 26 80-06 15 (13-17)Kvädöfjärden 107 11 95-05 9.6 (3.5, 16)* 25 (18-37)

Guillemot eggSt. Karlsö 255 34 69-06 -1.5 (-2.3, -.82) 260 (230-310)

# confidence interval based on only two-three years d.f = n of obs. -1, in all other cases d.f.= n of years -1


53

Hg, ng/g fresh wt., herring muscle

Harufjarden (3-4)

0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

n(tot)=412,n(yrs)=26m=38.7 (34.7,43.1)slope=-.20%(-1.6,1.2)SD(lr)=7.48,2.1%,16 yrpower=1.0/.29/10%y(06)=37.7 (30.5,46.6)r2=.00, NStao=.03, NSSD(sm)=8.59, NS,12%slope=2.3%(-6.1,11)SD(lr)=9.37,12%,18 yrpower=.21/.21/12%r2=.05, NS

Angskarsklubb (3-5)

0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

n(tot)=427,n(yrs)=26m=54.5 (42.5,70.0)slope=-2.1%(-5.2,1.0)SD(lr)=15.2,4.7%,25 yrpower=.85/.09/24%y(06)=41.8 (26.1,66.8)r2=.07, NStao=-.22, NSSD(sm)=13.3, NS,20%slope=-3.4%(-18,11)SD(lr)=13.7,21%,24 yrpower=.10/.10/21%r2=.04, NS

Landsort (3-5)

0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

n(tot)=406,n(yrs)=27m=28.5 (24.8,32.8)slope=1.6%(-.12,3.3)SD(lr)=10.0,2.5%,18 yrpower=1.0/.20/13%y(06)=35.1 (27.0,45.5)r2=.13, p<.064tao=.15, NSSD(sm)=8.21, p<.042,10%slope=-7.3%(-10,-4.3)SD(lr)=3.50,4.4%,10 yrpower=.90/.90/4.4%r2=.79, p<.001 *

Utlangan (2-4)

0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

n(tot)=424,n(yrs)=27m=17.3 (14.9,20.1)slope=.51%(-1.4,2.5)SD(lr)=13.4,2.8%,19 yrpower=1.0/.17/14%y(06)=18.5 (13.8,24.8)r2=.01, NStao=.09, NSSD(sm)=11.0, p<.043,12%slope=1.9%(-8.7,12)SD(lr)=14.6,16%,20 yrpower=.15/.15/16%r2=.02, NS

pia - 08.03.12 16:13, HGC

The blue lines indicate the suggested limit in children food by SNFA.

Hg, ng/g fresh wt., herring muscle

Angskarsklubb, spring


0

20

40

60

80

100

120

140

160

180

70 80 90 00

m=33.0 (26.1,41.9)slope=-2.8%(-3.9,-1.7)SD(lr)=7.01,4.5%,15 yrpower=.88/.35/9.0%y(06)=23.5 (19.4,28.5)r2=.70, p<.001 *tao=-.54, p<.005 *SD(sm)=8.20, NS,11%slope=-.70%(-7.0,5.6)SD(lr)=7.65,9.1%,15 yrpower=.34/.34/9.1%r2=.01, NS

Karlskrona, spring


0

20

40

60

80

100

120

140

160

180

70 80 90 00

m=20.1 (17.6,23.0)slope=-1.0%(-1.9,-.15)SD(lr)=6.38,4.0%,13 yrpower=.95/.53/7.0%y(06)=17.6 (15.0,20.7)r2=.35, p<.025 *tao=-.45, p<.025 *SD(sm)=6.80, NS,7.4%slope=.47%(-5.4,6.3)SD(lr)=7.56,9.7%,14 yrpower=.31/.41/8.1%r2=.01, NS

Fladen (2-3)


0

20

40

60

80

100

120

140

160

180

75 80 85 90 95 00 05

m=25.2 (22.5,28.2)slope=1.4%(.05,2.7)SD(lr)=8.21,1.9%,15 yrpower=1.0/.30/9.7%y(06)=30.3 (24.7,37.1)r2=.15, p<.040 *tao=.28, p<.043 *SD(sm)=6.97, p<.070,8.2%slope=5.9%(-.92,13)SD(lr)=8.23,9.8%,15 yrpower=.30/.30/9.8%r2=.33, p<.079

Vaderoarna


0

20

40

60

80

100

120

140

160

180

94 96 98 00 02 04 06

m=25.4 (21.1,30.4)slope=5.6%(1.1,10)SD(lr)=6.43,6.4%,13 yrpower=.59/.46/7.6%y(05)=33.5 (25.7,43.7)r2=.47, p<.020 *tao=.42, p<.073SD(sm)=5.18, p<.091,6.1%

pia - 08.03.27 09:30, HGV


54

Hg, ng/g fresh w., cod muscle


0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

n(tot)=402,n(yrs)=28m=29.9 (26.8,33.4)slope=2.2%(1.1,3.3)SD(lr)=6.66,1.6%,14 yrpower=1.0/.40/8.3%y(06)=40.3 (34.0,47.8)r2=.40, p<.001 *tao=.47, p<.001 *SD(sm)=5.53, p<.050,6.8%slope=4.3%(.56,8.1)SD(lr)=4.12,5.3%,11 yrpower=.75/.75/5.3%r2=.47, p<.028 *

Cod (2-3), Fladen

0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

n(tot)=447,n(yrs)=28m=53.1 (48.6,58.0)slope=.45%(-.65,1.6)SD(lr)=5.79,1.6%,14 yrpower=1.0/.39/8.4%y(06)=56.4 (47.4,67.2)r2=.03, NStao=.13, NSSD(sm)=4.19, p<.006,6.0%slope=-.95%(-6.7,4.8)SD(lr)=5.57,8.2%,14 yrpower=.40/.40/8.2%r2=.02, NS

pia - 08.03.12 16:25, HGG


Hg, ng/g fresh w., perch muscle

Holmoarna (3-6)


0

20

40

60

80

100

120

140

160

180

90 95 00 05

m=64.8 (55.3,76.0)slope=-.24%(-4.1,3.7)SD(lr)=6.28,7.0%,15 yrpower=.52/.31/9.6%y(06)=63.9 (47.4,86.1)r2=.00, NStao=-.03, NSSD(sm)=6.18, NS,9.4%slope=-.23%(-7.6,7.1)SD(lr)=6.80,13%,16 yrpower=.20/.27/10%r2=.00, NS

Kvadofjarden (3-6)


0

20

40

60

80

100

120

140

160

180

80 85 90 95 00 05

m=36.3 (30.5,43.2)slope=-3.3%(-5.2,-1.4)SD(lr)=9.37,3.0%,18 yrpower=1.0/.20/13%y(06)=24.1 (18.3,31.8)r2=.37, p<.002 *tao=-.39, p<.007 *SD(sm)=6.02, p<.002,7.9%slope=8.9%(3.5,14)SD(lr)=6.32,9.1%,13 yrpower=.34/.46/7.6%r2=.68, p<.006 *

pia - 08.03.13 13:25, HGP


55

Hg, n/g fresh w., eelpout

Holmoarna


0

20

40

60

80

100

120

140

160

180

94 96 98 00 02 04 06

m=81.6 (69.7,95.6)slope=-2.4%(-7.2,2.4)SD(lr)=5.29,7.2%,14 yrpower=.49/.38/8.5%y(06)=72.3 (54.1,96.8)r2=.12, NStao=-.31, NSSD(sm)=5.71, NS,9.2%

Kvadofjarden


0

20

40

60

80

100

120

140

160

180

94 96 98 00 02 04 06

m=76.9 (64.6,91.4)slope=-.17%(-5.5,5.2)SD(lr)=6.59,7.7%,16 yrpower=.45/.27/11%y(06)= 76 ( 54, 108)r2=.00, NStao=-.03, NSSD(sm)=5.07, p<.062,8.0%

Vaderoarna


0

20

40

60

80

100

120

140

160

180

94 96 98 00 02 04 06

m=25.2 (18.3,34.6)slope=10%(3.1,17)SD(lr)=11.4,10%,19 yrpower=.29/.18/14%y(06)=43.5 (27.9,68.0)r2=.51, p<.009 *tao=.42, p<.055SD(sm)=8.62, p<.053,10%

pia - 08.03.12 16:30, hgz


Hg, ng/g fresh wt., blue mussel soft body

Fladenn(tot)=473,n(yrs)=24

0

5

10

15

20

25

30

35

40

45

50

55

80 85 90 95 00 05

m=14.1 (12.5,16.0)slope=1.0%(-.65,2.7)SD(lr)=11.1,2.6%,16 yrpower=1.0/.25/11%y(06)=16.0 (12.6,20.2)r2=.07, NStao=.04, NSSD(sm)=6.95, p<.001,6.7%slope=9.1%(.07,18)SD(lr)=13.1,13%,18 yrpower=.19/.19/13%r2=.40, p<.047 *

Vaderoarnan(tot)=499,n(yrs)=26

0

5

10

15

20

25

30

35

40

45

50

55

80 85 90 95 00 05

m=14.8 (12.8,17.2)slope=.18%(-1.8,2.1)SD(lr)=14.0,2.9%,19 yrpower=1.0/.17/14%y(06)=15.2 (11.3,20.4)r2=.00, NStao=-.02, NSSD(sm)= 9.9, p<.005,9.8%slope=10%(3.4,17)SD(lr)=10.0,9.9%,15 yrpower=.29/.29/9.9%r2=.60, p<.009 *

Kvadofjardenn(tot)=107,n(yrs)=11

0

5

10

15

20

25

30

35

40

45

50

55

94 96 98 00 02 04 06

m=15.7 (11.8,20.8)slope=9.6%(3.5,16)SD(lr)=10.3,8.8%,16 yrpower=.35/.27/10%y(05)=25.4 (17.7,36.5)r2=.59, p<.006 *tao=.64, p<.006 *SD(sm)=10.5, NS,11%

pia - 08.03.13 08:20, HGM

The blue lines indicate background concentration in OSPAR areas.

56

Hg, ng/g fresh w., guillemot eggs, early laid

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

70 75 80 85 90 95 00 05

n(tot)=255,n(yrs)=34m=350 (317 ,386 )slope=-1.5%(-2.3,-.82)SD(lr)=3.85,1.2%,14 yrpower=1.0/.40/8.2%y(06)= 264 ( 227, 308)r2=.37, p<.001 *tao=-.45, p<.001 *SD(sm)=2.57, p<.001,5.4%slope=.04%(-4.4,4.5)SD(lr)=3.05,6.3%,12 yrpower=.61/.61/6.3%r2=.00, NS

pia - 08.03.12 16:34, HGU

57

12 LeadUpdatated 08.03.28


The toxic effects of lead involve several organ system and biochemical activities and themajor risk is its toxicity to the nervous system. The risk is highest for Children and unborn,partly because of higher permeability of the blood-brain barrier (Klaassen & Rozman,1991).

Lead is known to concentrate in liver tissue but to an even greater extent in the bone matrix.Approximately 90% of the total amount of lead in humans are found in the skeleton(Klaassen & Rozman, 1991). The lead concentration in liver from Baltic herring is about 4times higher (wet wt.) than the concentration reported for the edible parts of herring. Forcod, the concentration in liver is about 2.5 times higher and for perch about 2 times.Concentrations in edible parts are reported by Jorhem and Sundström, 1993.

Lead is one of the mandatory contaminants that should be analysed and reported withinboth the OSPARCOM and HELCOM conventions.

The concentration of lead in fish liver and blue mussel soft body is determined using anatomic absorption spectrophotometer with graphite furnace at the Department ofEnvironmental Assessment at Swedish University of Agricultural Sciences. The detectionlimit is estimated to approximately 10 ng/g dry weight which implies that theconcentrations in herring, flounder and dab are approximately 10-20 times above thedetection limit.

The estimated residual variance is higher in the beginning of the time series. 1982 seems tobe lower than the surrounding years in all series but one, indicating an analytical problem.


Year CRM n % %

90 DOLT-1 12 14 -6.191 DOLT-1 12 13 -8.193 DOLT-2 17 7.4 -1.794 DOLT-2 12 6.9 3.695 DOLT-2 3 4.5 1.597 SLRS-3 9 9.0 1.8

The uncertainty of a single analytical value is thus estimated to be between 5-15%. Themean deviation (including the sign) of the analysed CRM samples, from the standard valueis between 1-10%.

58



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the lead discharges are to be reduced by 70% between 1985 and 1995,using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of thedischarges of lead to air and water by 50% by 1995 with 1987 as a base year.

12.1.2 Other investigations

Jorhem and Sundström (1993) found about 75% lower levels of lead in fish samples (Balticherring, cod and pike) from the period 1983-90 compared to a previous study from theperiod 1973-82 (Jorhem et al. 1984).


At Harufjärden, Ängskärsklubb (autumn), Landsort, Utlängan and Fladen, the investigatedtime series in herring liver show significant decreasing trends.

The number of years required to detect an annual change of 5% varied between 9 to 19years for the herring time series with a power to detect a 5% annual change ranging from0.19 (shorter series) to 1.0 (longer series). An annual change greater than 10% would likelybe detected.

Lead concentrations in cod liver (after adjusting for varying fat content) showed decreasingtrends from SE Gotland and Fladen.

Lead concentrations in the shorter time series of perch liver showed decreasing trends fromKvädöfjärden but not for Holmöarna.

The short time series (8 years) of lead in guillemot eggs show a significant decreasing trend.

The lead concentration in blue mussel soft body from Fladen showed a significantdecreasing trend and the short time series from Kvädöfjärden a significant increasing trend.

12.1.4 Conclusion

The decrease of lead in most matrices at most sampling sites probably reflects a generaldecrease of lead in the environment.


The lead concentration in blue mussels from the Swedish west coast is not significantlyhigher compared to blue mussel samples of similar length from a reference site at

59

Kobbefjord, Greenland (Riget et al 1993). Mussel samples from all three sites show meanlevels below the ‘background concentration at diffuse loading’ in blue mussels for lead of<5 g/g dry weight, proposed by Knutzen and Skie (1992).


Significant differences in mean lead concentration (g/g dry weight), in fish liver and bluemussel soft body, were found between the species marked with '>‘:

Holmöarna: Eelpout(0.14) > Perch(0.04)Kvädöfjärden: Blue mussel (4.3) > Eelpout(0.18) > Perch(0.033)Fladen: Blue mussel(0.86) > Herring(0.08) > Cod(0.04)Väderöarna: Blue mussel(1.1) > Eelpout(0.14) > Herring(0.044)

The lead concentration in blue mussel soft body tissue is thus generally much higher thanconcentration in fish liver. The concentration in eelpout liver is about three to five timeshigher than perch liver in the analysed samples.

The recommended limit for children’s food is set by the Swedish Food Administration to 50ng/g fresh weight (SLVFS, 1993). Within the European Community the limit in fish muscleis set to 0.2 ug/g and in mussels to 1.5 ug/g. (EG, 2002).

60

Table 12.2. Estimated geometric mean concentrations of lead (ug/g dry weight) for the last sampled year invarious matrices and sites during the investigated time period. The age interval for fish, and the length intervalfor blue mussels are also presented together with the total number of analyses and the number of years of thevarious time-series.

Matrix age n n yrs year trend (95% ci) last year (95% ci)Herring liverHarufj. autumn 3-4 357 21 81-03 -5.2(-7.2, -3.3)* 0.064 (.050-.083)Ängskärskl. aut. 3-5 383 22 81-03 -4.2 (-6.2, -2.1)* .099 (.077-.13)

” spring 3-6 80 8 96-03 .18 (.15-.21)Landsort 3-5 370 23 81-03 -5.1 (-7.1,-3.1)* .11 (.081-.14)Utlängan, aut. 2-4 307 23 81-03 -2.2 (-4.8, .35) .15 (.11-.21)

” spring 0 -4 47 5 96-03 .19 (.17-.21)Fladen 2-3 443 23 81-03 -4.2 (-6.6, -1.8)* .080 (.059, 0.11)Väderöarna 2-4 180 9 95-03 .056 (.044-.072)

Cod liverSE Gotland 3-4 339 23 81-03 -7.2 (-9.9,-4.5)* .021 (.014-.030)Fladen 2-4 425 23 81-03 -5.1 (-7.8,-2.4)* .040 (.029-.057)

Perch liverHolmöarna 0-7 90 9 95-03 .048 (.035-.065)Kvädöfjärden 3-7 80 8 95-03 -10 (-17,-3.0)* .033 (.023-.047)

Eelpout liverHolmöarna 67 7 95-03 .16 (.12-.20)Kvädöfjärden 89 9 95-03 .19 (.17-.21)Väderöarna 79 8 95-03 .13 (.10-.17)

Dab liverFladen 3-6 257 14 81-94 .77 (-3.0, 4.6)* 221 (165-296)

Flounder liverVäderöarna 4-6 239 14 81-94 -0.06 (-5.4,5.3)* 173 (115-260)

Blue mussel shell lFladen 5-8 396 21 81-03 -4.4 (-8.6-.12)* .86(.51-1.5)Väderöarna 6-10 412 22 81-03 1.4 (1.1-1.8)Kvädöfjärden 88 9 95-03 19 (1.3, 36)* 4.3 (1.9-9.8)

Guillemot eggSt. Karlsö 80 8 96-03 -13 (-18,-8.7)* .030 (.025-.037)


61

Pb, ug/g dry w., herring liver

Harufjarden (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=357,n(yrs)=21m=.113 (.091,.141)slope=-5.2%(-7.2,-3.3)SD(lr)=13.8,3.3%,16 yrpower=.99/.25/11%y(03)=.064 (.050,.083)r2=.62, p<.001 *tao=-.69, p<.001 *SD(sm)=15.7, NS,13%slope=-6.2%(-14,1.9)SD(lr)=12.4,12%,17 yrpower=.23/.23/12%r2=.28, NS

Angskarsklubb (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=383,n(yrs)=22m=.156 (.130,.188)slope=-4.2%(-6.2,-2.1)SD(lr)=16.7,3.1%,17 yrpower=1.0/.23/12%y(03)=.099 (.077,.129)r2=.47, p<.001 *tao=-.47, p<.002 *SD(sm)=13.8, p<.061,9.4%slope=-8.8%(-18,.41)SD(lr)=17.1,14%,18 yrpower=.18/.18/14%r2=.38, p<.057

Landsort (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=370,n(yrs)=23m=.184 (.151,.224)slope=-5.1%(-7.1,-3.1)SD(lr)=18.0,2.9%,17 yrpower=1.0/.24/11%y(03)=.105 (.081,.135)r2=.58, p<.001 *tao=-.49, p<.001 *SD(sm)=16.7, NS,10%slope=-6.6%(-16,3.0)SD(lr)=18.2,14%,19 yrpower=.17/.17/14%r2=.24, NS

Utlangan (2-4)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=307,n(yrs)=23m=.195 (.163,.233)slope=-2.2%(-4.8,.35)SD(lr)=24.2,3.7%,19 yrpower=.97/.16/15%y(03)=.152 (.109,.212)r2=.13, p<.083tao=-.45, p<.003 *SD(sm)=29.6, NS,18%slope=-3.4%(-11,4.6)SD(lr)=17.3,12%,17 yrpower=.23/.23/12%r2=.11, NS

pia - 08.03.18 09:56, PBC

Pb, ug/g dry weight, herring liver

Angskarsklubb,spring

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

96 98 00 02 04 06

age=3-6n(tot)=80,n(yrs)=8m=.177 (.150,.208)slope=4.3%(-2.4,11)SD(lr)=10.4,9.7%,12 yrpower=.31/.58/6.5%y(03)=.206 (.155,.273)r2=.29, NStao=.36, NS

Karlskrona,spring

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

96 98 00 02 04 06

age=3-4n(tot)=47,n(yrs)=5m=.186 (.166,.207)slope=-.90%(-7.5,5.7)SD(lr)=5.86,14%,9 yrpower=.20/.98/3.5%y(03)=.180 (.140,.232)r2=.06, NStao=.00, NS

Fladen (2-3)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=443,n(yrs)=23m=.127 (.104,.155)slope=-4.2%(-6.6,-1.8)SD(lr)=17.6,3.4%,18 yrpower=.99/.18/14%y(03)=.080 (.059,.109)r2=.39, p<.001 *tao=-.57, p<.001 *SD(sm)=18.7, NS,14%slope=-7.5%(-13,-1.9)SD(lr)=9.31,8.1%,14 yrpower=.41/.41/8.1%r2=.54, p<.015 *

Vaderoarna

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=2-4n(tot)=180,n(yrs)=9m=.056 (.044,.072)slope=-6.3%(-15,2.7)SD(lr)=10.3,13%,16 yrpower=.19/.25/11%y(03)=.044 (.028,.067)r2=.28, NStao=-.33, NS

pia - 08.03.27 09:31, PBV

62

Pb, ug/g dry w., cod liverFat adjusted geometric means

Cod, SE Gotland (3-4)


.00

.05

.10

.15

.20

.25

.30

.35

80 85 90 95 00 05

m=.047 (.036,.063)slope=-7.2%(-9.9,-4.5)SD(lr)=13.6,3.9%,20 yrpower=.96/.15/16%y(03)=.021 (.014,.030)r2=.60, p<.001 *tao=-.73, p<.001 *SD(sm)=12.8, NS,15%

slope=-7.6%(-21,5.9)SD(lr)=15.3,21%,23 yrpower=.11/.11/21%r2=.17, NS

Cod, Fladen (2-4)


.00

.05

.10

.15

.20

.25

.30

.35

80 85 90 95 00 05

m=.071 (.056,.089)slope=-5.1%(-7.8,-2.4)SD(lr)=15.5,3.8%,20 yrpower=.96/.15/15%y(03)=.040 (.029,.057)r2=.43, p<.001 *tao=-.52, p<.001 *SD(sm)=15.1, NS,15%

slope=-1.2%(-9.4,6.9)SD(lr)=10.7,12%,17 yrpower=.22/.22/12%r2=.02, NS

pia - 08.03.26 10:06, PBG

Pb, ug/g dry w. perch

Holmoarna

.00

.02

.04

.06

.08

.10

.12

.14

94 96 98 00 02 04 06

age=0-7n(tot)=90,n(yrs)=9m=.048 (.035,.065)slope=-6.7%(-18,4.7)SD(lr)=12.3,17%,19 yrpower=.14/.17/14%y(03)=.037 (.021,.063)r2=.22, NStao=-.22, NS

Kvadofjarden

.00

.02

.04

.06

.08

.10

.12

.14

94 96 98 00 02 04 06

age=3-7n(tot)=80,n(yrs)=8m=.050 (.038,.068)slope=-10%(-17,-3.0)SD(lr)=7.32,12%,14 yrpower=.22/.42/8.0%y(03)=.033 (.023,.047)r2=.67, p<.014 *tao=-.71, p<.013 *

pia - 08.03.19 08:46, PBP

63

Pb, ug/g wet w., blue mussel softbodyShell lengths in brackets

Fladen (5-8 cm)

.0

.5

1.0

1.5

2.0

2.5

3.0

80 85 90 95 00 05

n(tot)=396,n(yrs)=21m=.202 (.147,.279)slope=-6.1%(-10,-2.0)SD(lr)=37.0,6.4%,25 yrpower=.58/.10/23%y(03)=.107 (.065,.178)r2=.34, p<.005 *tao=-.34, p<.030 *SD(sm)=26.5, p<.013,16%slope=-16%(-22,-8.9)SD(lr)=14.7,9.7%,15 yrpower=.31/.31/9.7%r2=.78, p<.001 *

Vaderoarna (6-10 cm)

.0

.5

1.0

1.5

2.0

2.5

3.0

80 85 90 95 00 05

n(tot)=412,n(yrs)=22m=.229 (.186,.281)slope=-1.5%(-4.5,1.5)SD(lr)=31.5,4.7%,21 yrpower=.86/.13/18%y(03)=.194 (.131,.288)r2=.05, NStao=-.30, p<.052SD(sm)=32.4, NS,18%slope=-1.3%(-13,11)SD(lr)=30.3,18%,22 yrpower=.12/.12/18%r2=.01, NS

Kvadofjarden

.00

.25

.50

.75

1.00

1.25

1.50

1.75

94 96 98 00 02 04 06

length=0-3n(tot)=88,n(yrs)=9m=.257 (.204,.323)slope=19%(11,27)SD(lr)=71.3,1.2%,34 yrpower=1.0/.07/40%r2=.20, p<.001 *tao=.33, p<.001 *

pia - 08.03.19 09:32, PBWM


Pb, ug/g dry w. Guillemot egg

Stora Karlso

n(tot)=80,n(yrs)=8

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

94 96 98 00 02 04 06

m=.048 (.043,.055)slope=-13%(-18,-8.7)SD(lr)=15.7,.70%,22 yrpower=1.0/.12/18%y(03)=.030 (.025,.037)r2=.30, p<.001 *

pia - 08.03.19 10:12, pbu

64

13 CadmiumUpdated 08.03.28


Cadmium is an important metal in many industrial applications. It has been excessivelyused until the end of the seventies, in electroplating or galvanising because of itsnoncorrosive properties. It is has also been used (and is still used to some extent) as acathode material for nickel-cadmium batteries and as a colour pigment for paints andplastics. Its industrial use has however decreased considerable during recent years. In 1982,Sweden as the first country in the world introduced a principal ban for certain industrialapplications. Cadmium does also reach the environment as a by-product of zinc and leadmining and smelting and as an undesired element in fertilisers.

Cadmium is one of the mandatory contaminants that should be analysed and reportedwithin both the OSPARCOM and the HELCOM conventions.

The time series of cadmium concentration in fish liver and blue mussel soft body, presentedbelow, start 1981. It is determined using an atomic absorption spectrophotometer withgraphite furnace at the Department of Environmental Assessment at Swedish University ofAgricultural Sciences. The detection limit is estimated to approximately 5 ng/g dry weight.


Year CRM n % %

90 Dolt-1 4 6.3 6.391 Dolt-1 15 4.0 -0.593 Dolt-2 20 4.1 0.594 Dolt-2 21 3.3 1.795 Dolt-2 22 2.7 -0.196 Dolt-2 24 5.5 2.497 Dolt-2 6 4.9 -2.4

The uncertainty of a single analytical value is thus estimated to be around 5% on averageand has not changed over time. The mean deviation (including the sign) of around 20samples from the standard value is (except for 1990) less than 2.5% and shows nosystematic deviation. Although the concentration of cadmium in Dolt2 is about 10 to 15times higher compared to the levels in the investigated herring livers, there is no reason,sofar, to believe that the impact from analytical errors on the evaluation of the time series isimportant.

65



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the cadmium discharges are to be reduced by 70% between 1985 and1995, using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of thedischarges of cadmium to air and water by 50% by 1995 with 1987 as a base year.

The Swedish Parliament has agreed on a general reduction of cadmium discharges aimingat a reduction of 70% between 1985 and 1995. Further, that all use of cadmium that impliesa risk of discharges to the environment, in a longer term perspective, will cease (prop1990/91:90, JoU 30, rskr.343).

In 1982, the use of cadmium in electroplating and as a thermal stabilisor was banned inSweden.

A fee on batteries containing cadmium was introduced 1987 in Sweden. This fee was raisedconsiderably in 1991.

The content of cadmium in fertilisers was restricted to 100g/ton phosphorus, 1993.01.01 inSweden.

13.1.2 Input

The discharges of cadmium to the environment in Sweden have been estimated to havedecreased with approximately 45% between 1985 and 1990 while the airborne cadmiumload during the same period is estimated to have decreased with approximately 15% (SNV,Rapport 4135). The river discharges to the Baltic from Sweden have decreased considerablyduring the recent decades while from Poland, Russia and the Baltic countries the dischargesare still very high. The estimated cadmium burden (in tons) 1990 from Sweden compared toall countries was, to; the Bothnian Bay and the Bothnian Sea, 2/17; the Baltic proper0.41/110; the Kattegatt, 0.5/6(Widell, 1990,1992).

13.1.3 Proposed processes

a) Decreased contaminant load may cause a corresponding decrease in the amountbioavaillable cadmium.

b) Bengtsson (1975) among others, suggested that decreasing salinity increase thebioavailability of cadmium. Studies by Danielsson et al.(1983), Mart et al.(1985) andNolting (1986) show that cadmium is desorbed from particulate material during transitionfrom fresh to more saline water. Hence, plankton may gain in adsorption capacity as salinitydecrease. Decreasing levels of salinity during the period have been reported from severalstations in the Baltic (Bergström & Matthäus, 1995) but also in the Bothnian Bay. Herringfeeding on plankton may thus be exposed to increasing levels of bioavaillable cadmium(Harms, 1995).

c) Increased mobility of Cd-ions due to acidification may cause an increased cadmiumconcentration in the run off (e.g. Borg et al, 1989).

66

d) Cadmium can be bound to metallothionein (MT) (da Silva and Williams, 1994). It isfurther known that various compounds can induce (and possibly also inhibit) the formationof MT in fish liver (Bouquegneau et al., 1975). A change in the amount of MT, due toinduction, inhibition or ceased induction or inhibition, might thus change the metalconcentration in the analysed liver tissue.


Concentrations of dissolved and particulate cadmium were determined in seawater fromseveral sites in the Baltic proper for nine years during the time period 1980 to 1993 (Pohl,1994, Schneider & Pohl, 1995). The material was separated into two regions. A decrease ofapproximately 7% per year was found in the Mecklenburg Bight/Arkona Sea and in surfacewaters of the Bornholm Sea/Gotland Sea. The time series are however based on data fromvarious seasons and the analytical technique has changed over time.

Cadmium concentration analysed in herring muscle between 1979 to 1993 from threeFinnish sites: western and eastern Gulf of Finland and southern Bothnian Bay showdecreasing trends of between 10 to 12% a year (ICES, 1995). However, the analysedcadmium concentrations are close to, and for several years below, the detection limit.

Cadmium concentration in herring muscle has also been reported from three sites along thePolish coast between 1974-1988 (Protasowicki et al. 1975) and during 1991-1993 (Polak-Juszczak and Domagala, 1994) where the mean values indicate a decrease. Polish data ofCd concentrations analysed in herring muscle and liver from three sites were also reportedto HELCOM and assessed by ICES but were found too short to disclose any trends (ICES,1995).

A general remark for extra cautiousness is appropriate when interpreting analyses of lowconcentrations near the detection level as in water or muscle samples. An improved analytictechnique may lead to decreasing concentrations due to less risk of sample contamination.


Cadmium concentrations in herring liver from Utlängan (autumn) in the Baltic proper showa significant increasing log-linear trend. The total increase in cadmium concentrationduring 1981-95 at Ängskärsklubb, Landsort and Utlängan is about 2.5 times. During recentyears the increases have levelled out and also turned to a decrease at least at Landsort andÄngskärsklubb.Cadmium concentrations in cod liver samples (adjusted for varying fat content) from southeast of Gotland and Fladen show significant decreasing trends .

Cadmium concentrations in eelpout samples from Holmöarna, Kvädöfjärden andVäderöarna all show significant increasing trends (the between year variation at Holmöarnaand Kvädöfjärden is large though).

The number of years required to detect an annual change of 5% varied between 10 to 19years for the herring time series with a power to detect a 5% annual change ranging from0.46 to 1.0. (Since it is not appropriate to fit a log-linear trend at Ängskärsklubb andUtlängan, these sites were excluded from the power calculations.)

The geometric mean concentration of cadmium in dab liver was extremely high in 1988,about 5 times the overall mean concentration.

67

13.1.6 Conclusion

The rapid increase of cadmium concentrations at Ängskärsklubb and Landsort seems tohave stopped and is now turning downwardCadmium is concentrated in internal organs, i.e. liver, why the concentration in muscletissue is very low. Analysed values for perch and herring muscle are 0.5 and 4 ng/g dryweight respectively (unpublished data). The average cadmium concentration in potatoes (ina sample of 8, during 1987-1990) was reported to 17 ng/g (Jorhem and Sundström, 1993).The cadmium concentrations of 0.5 to 4 ng/g indicates that there is no immediate risk forhuman consumption, since the EU limit suggested for human consumption of fish is 50ng/g fresh weight (EG nr 221/2002).



Cadmium analysed in kidney cortex from juvenile harbour seals showed significantly lowervalues in samples from the Baltic compared to comparable samples from the west coast(Frank et al. 1992)


The overall mean Cd-concentrations in herring liver from the Baltic show significantlyhigher cadmium concentrations compared to Fladen in the Kattegatt and Väderöarna in theSkagerack at the Swedish west coast. All sampling sites in the Baltic show significantlyhigher levels, estimated 2000, compared to Fladen. The geometric mean concentration inherring liver, for the period 1981-2003, from Harufjärden (Bothnian Bay) and Ladsort(Baltic proper) show about 3 repectively 3.5 times higher values compared to samples fromthe Kattegatt.

Eelpout livers from Holmöarna in the southern Bothnian Bay and Kvädöfjärden in theBaltic Proper show about 3 to 4 times higher geometric mean Cd-concentrations (dryweight) compared to samples from Väderöarna in the Skagerack.

Blue mussels from Kvädöfjärden, analysed 1995-03, show about 3 times higherconcentrations compared to blue mussel samples from the Swedish west coast. The samplesfrom the Swedish west coast show mean levels similar to what is found in blue musselsfrom the Belgian coast (Vyncke et al. 1999) and do not exceed the ‘high backgroundconcentration at diffuse loading’ for cadmium in blue mussels of <2 g/g dry weight,proposed by Knutzen and Skie (1992) whereas the samples from Kvädöfjärden does. Allblue mussel samples exceed the range of ‘present background concentrations in pristineareas within the OSPAR Convention Area’ proposed to 0.070-0.11 g/g wet weight (ICES,1997). The estimated geometric mean concentration from Kvädöfjärden exceeds thisconcentration by about 4 times.

Cadmium concentrations in cod livers from Fladen in the Kattegatt, are significantly higher(about 3 times on a dry weight basis and about 2 times on a fresh weight basis) compared tosamples from south east of Gotland. This may be explained by the fact that the average fatcontent in cod liver from Gotland is about 2.5 times higher compared to the samples fromthe Kattegatt. The Swedish data from SE of Gotland are in the same range as Finnish dataof cod liver from the Gulf of Finland and the Bothnian Sea.

68

Herring liver from Fladen in the Kattegatt show significantly higher concentrationscompared to Väderöarna in the Skagerack.


Significant differences in mean cadmium concentration (g/g dry weight), in fish liver andblue mussel soft body, were found between the species marked with '>' :

Holmöarna: Eelpout(1.8) > Perch(0.47)Kvädöfjärden: Blue mussel(4.3) > Eelpout(2.1) > Perch(0.60)Fladen: Blue mussel(0.96) > Herring(0.54) > Cod(0.12)Väderöarna: Blue mussel(1.1) > Herring(0.33) - Eelpout(0.49)

The cadmium concentration in blue mussel soft body tissue is thus about 2 to 9 times theconcentration found in fish liver and the concentration in eelpout liver is about twice ashigh as in perch liver in the analysed samples. The concentration found in guillemot egg isextremely low, at least 500 times lower (dry weight) compared to herring liver.

Table 13.2. Geometric mean concentrations of cadmium (g/g dry weight) in various matrices and sitesduring the whole investigated time period and the estimated mean concentration for the last year. The ageinterval for fish, and the length interval for blue mussels are also presented together with the total number ofanalyses and the number of years of the various time-series.

Matrix age n n yrs year trend (95% ci) last year (95% ci)Herring liverHarufj. autumn 3-4 364 22 81-03 1.4 (1.2-1.7)Ängskärskl. aut. 3-5 382 22 81-03 3.0 (.75, 5.2)* 2.3 (1.7-3.1)

” spring 3-6 80 8 96-03 3.9 (3.3-4.7)Landsort 3-5 370 23 81-03 1.8 (-.25, 3.9) 2.3 (1.8-3.1)Utlängan, aut. 3-4 287 23 81-03 3.1 (1.3, 4.8)* 2.4 (1.9-3.0)

” spring 0-4 70 7 96-03 2.4 (2.1-2.7)Fladen 2-3 443 23 3 .54 (.48-.59)Väderöarna 2-4 180 9 95-03 .33 (.29-.38)

Cod liverSE Gotland 3-4 343 23 81-03 -6.4 (-8.3,-4.5)* .027 (.021-.035)Fladen 2-4 426 23 81-03 -3.5 (-6-4,-.60)* .12 (.079-.17)

Perch liverHolmöarna 0-7 90 9 95-03 .47 (.35-.62)Kvädöfjärden 90 9 95-03 .60 (.47-.77)

Eelpout liverHolmöarna 67 7 95-03 11 (4.7, 17)* 1.8 (1.4-2.3)Kvädöfjärden 2-9 89 9 95-03 10 (4.7, 16)* 2.1 (1.6-2.7)Väderöarna 3-8 79 8 95-03 11 (5.6, 17) .49 (.38-.63)

Dab liverFladen 3-6 257 14 81-94 3.7 (-4.8,12)* 0.81 (.42-1.5)

Flounder liverVäderöarna 4-6 239 14 81-94 1.7 (-3.7,7.0)* 0.53 (.35-.80)

Blue mussel shell lFladen 5-8 396 21 81-03 -1.3 (-2.7, .19) .96 (.80-1.2)Väderöarna 6-10 413 22 81-03 1.1 (.94-1.2)Kvädöfjärden 0-3 88 9 95-03 4.3 (3.8-4.8)

Guillemot eggSt. Karlsö 78 8 96-03 -16 (-25,-7.1)* .001 (.001-.002)


69

Cd, ug/g dry w., herring liver

Harufjarden (3-4)


.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

85 90 95 00 05

m=1.42 (1.19,1.69)slope=.75%(-1.9,3.4)SD(lr)=113 ,4.0%,19 yrpower=.95/.16/15%y(03)=1.54 (1.10,2.15)r2=.02, NStao=.11, NSSD(sm)=114 , NS,15%slope=11%(.00,22)SD(lr)=141 ,17%,21 yrpower=.14/.14/17%r2=.40, p<.048 *

Angskarsklubb (3-5)


.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

85 90 95 00 05

m=1.67 (1.41,1.98)slope=3.0%(.75,5.2)SD(lr)=64.8,3.4%,17 yrpower=.99/.21/12%y(03)=2.30 (1.74,3.05)r2=.28, p<.011 *tao=.37, p<.017 *SD(sm)=55.5, p<.096,11%slope=-2.6%(-10,5.1)SD(lr)=45.2,11%,16 yrpower=.24/.24/11%r2=.07, NS

Landsort (3-5)


.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

85 90 95 00 05

m=1.92 (1.66,2.22)slope=1.8%(-.25,3.9)SD(lr)=48.3,3.0%,17 yrpower=1.0/.23/12%y(03)=2.34 (1.80,3.05)r2=.14, p<.079tao=.35, p<.019 *SD(sm)=30.2, p<.002,7.1%slope=-6.7%(-15,2.0)SD(lr)=44.7,13%,18 yrpower=.20/.20/13%r2=.28, NS

Utlangan (3-4)


.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

85 90 95 00 05

m=1.73 (1.50,2.00)slope=3.1%(1.3,4.8)SD(lr)=49.1,2.5%,15 yrpower=1.0/.30/9.9%y(03)=2.43 (1.94,3.04)r2=.39, p<.002 *tao=.42, p<.005 *SD(sm)=40.5, p<.059,8.1%slope=1.2%(-6.0,8.4)SD(lr)=40.5,10%,16 yrpower=.27/.27/10%r2=.02, NS

Contaminant Research Group /NRM, Dep.Env.Assess./SLU 08.03.19 08:52, CDC

Cd, ug/g dry weight, herring liver

Anskarsklubb, spring

0

1

2

3

4

5

6

7

96 98 00 02 04 06

age=3-6n(tot)=80,n(yrs)=8m=3.92 (3.28,4.68)slope=-.88%(-9.5,7.7)SD(lr)=16.7,13%,14 yrpower=.21/.39/8.3%y(03)=3.80 (2.65,5.45)r2=.01, NStao=-.21, NS

Karlskrona, spring

0

1

2

3

4

5

6

7

96 98 00 02 04 06

age=0-4n(tot)=70,n(yrs)=7m=2.39 (2.12,2.69)slope=2.8%(-3.3,8.9)SD(lr)=14.4,8.6%,10 yrpower=.38/.88/4.5%y(02)=2.60 (2.09,3.23)r2=.22, NStao=.52, p<.099

Fladen (2-3)

0

1

2

3

4

5

6

7

80 85 90 95 00 05

n(tot)=443,n(yrs)=23m=.535 (.484,.592)slope=.69%(-.84,2.2)SD(lr)=37.6,2.2%,14 yrpower=1.0/.37/8.6%y(03)=.578 (.474,.704)r2=.04, NStao=.04, NSSD(sm)=38.3, NS,8.7%slope=2.4%(-2.8,7.6)SD(lr)=33.1,7.4%,13 yrpower=.48/.48/7.4%r2=.13, NS

Vaderoarna

0

1

2

3

4

5

6

7

94 96 98 00 02 04 06

age=2-4n(tot)=180,n(yrs)=9m=.334 (.291,.384)slope=2.9%(-2.4,8.2)SD(lr)=15.9,7.6%,12 yrpower=.46/.61/6.3%r2=.19, NStao=.22, NS

pia - 08.03.27 09:27, CDV

70

Cd, ug/g dry w., cod liverFat adjusted geometric means

Cod, SE Gotland (3-4)


.0

.1

.2

.3

.4

.5

80 85 90 95 00 05

m=.055 (.044,.069)slope=-6.4%(-8.3,-4.5)SD(lr)=10.0,2.7%,16 yrpower=1.0/.26/11%y(03)=.027 (.021,.035)r2=.70, p<.001 *tao=-.68, p<.001 *SD(sm)=6.21, p<.001,6.5%

slope=-7.1%(-12,-2.5)SD(lr)=5.66,6.6%,12 yrpower=.57/.57/6.6%r2=.61, p<.007 *

Cod, Fladen (2-4)


.0

.1

.2

.3

.4

.5

80 85 90 95 00 05

m=.169 (.136,.209)slope=-3.5%(-6.4,-.60)SD(lr)=24.9,4.2%,21 yrpower=.93/.14/17%y(03)=.115 (.079,.167)r2=.23, p<.019 *tao=-.31, p<.037 *SD(sm)=15.6, p<.002,10%

slope=5.4%(-2.5,13)SD(lr)=14.6,11%,17 yrpower=.24/.24/11%r2=.24, NS

pia - 08.03.26 10:07, CDG

Cd, ug/g dry w. perch

Holmoarna

.00

.25

.50

.75

1.00

1.25

1.50

1.75

94 96 98 00 02 04

age=0-7n(tot)=90,n(yrs)=9m=.465 (.349,.620)slope=5.2%(-6.1,16)SD(lr)=48.4,17%,19 yrpower=.14/.18/14%y(03)=.573 (.334,.981)r2=.14, NStao=.17, NS

Kvadofjarden

.00

.25

.50

.75

1.00

1.25

1.50

1.75

94 96 98 00 02 04

n(tot)=90,n(yrs)=9m=.602 (.470,.771)slope=1.2%(-9.2,12)SD(lr)=67.5,15%,18 yrpower=.15/.20/13%y(03)= .63 ( .38,1.04)r2=.01, NStao=.06, NS

pia - 08.03.19 10:34, CDP

71

Cd, ug/g dry w., Eelpout

Holmoarna

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

94 96 98 00 02 04 06

n(tot)=67,n(yrs)=7m=1.25 (1.05,1.48)slope=11%(4.7,17)SD(lr)=287 ,1.2%,26 yrpower=1.0/.09/25%y(03)=1.77 (1.37,2.28)r2=.16, p<.001 *tao=.29, p<.001 *

Kvadofjarden

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

94 96 98 00 02 04 06

age=2-9n(tot)=89,n(yrs)=9m=1.38 (1.18,1.60)slope=10%(4.7,16)SD(lr)=210 ,.80%,27 yrpower=1.0/.09/26%y(03)=2.07 (1.59,2.68)r2=.14, p<.001 *tao=.34, p<.001 *

Vaderoarna

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

94 96 98 00 02 04 06

age=3-8n(tot)=79,n(yrs)=8m=.320 (.274,.375)slope=11%(5.6,17)SD(lr)=55.8,.90%,26 yrpower=1.0/.09/25%y(03)=.489 (.380,.629)r2=.18, p<.001 *tao=.29, p<.001 *

pia - 08.03.19 10:41, cdz

Cd, ug/g wet w., blue mussel softbodyShell lengths in brackets

Fladen (5-8 cm)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=396,n(yrs)=21m=.164 (.141,.190)slope=-3.0%(-4.8,-1.2)SD(lr)=14.4,2.8%,15 yrpower=1.0/.31/9.6%y(03)=.120 (.096,.150)r2=.39, p<.002 *tao=-.36, p<.022 *SD(sm)= 9.8, p<.007,6.4%slope=-1.3%(-7.4,4.8)SD(lr)=12.3,8.8%,14 yrpower=.36/.36/8.8%r2=.03, NS

Vaderoarna (6-10)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

80 85 90 95 00 05

n(tot)=413,n(yrs)=22m=.171 (.155,.188)slope=-.38%(-1.8,1.1)SD(lr)=12.4,2.2%,14 yrpower=1.0/.42/8.0%y(03)=.164 (.136,.197)r2=.02, NStao=.00, NSSD(sm)=8.87, p<.011,5.7%slope=3.7%(-1.2,8.6)SD(lr)=10.8,7.0%,13 yrpower=.52/.52/7.0%r2=.28, NS

Kvadofjarden

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

length=0-3n(tot)=88,n(yrs)=9m=.540 (.500,.582)slope=1.3%(-1.7,4.2)SD(lr)=57.8,.50%,18 yrpower=1.0/.19/13%y(03)=.567 (.494,.652)r2=.01, NStao=.13, p<.073

pia - 08.03.19 10:56, CDWM


72

14 NickelUpdated 08.03.28


The concentration of nickel in fish liver is determined using an atomic absorptionspectrophotometer with graphite furnace at the Department of Environmental Assessment atSwedish University of Agricultural Sciences. The detection limit is estimated toapproximately 0.1 g/g dry weight.

The analysis started on samples collected 1995.


The time series of herring from Landsort, Fladen and Väderöarna, cod liver from SEGotland and Fladen, perch liver from Holmöarna and eelpout from Kvädöfjärden andVäderöarna, all show significant decreasing trends.

Nickel has only been analysed since 1995 (eight years) and therefore the possibilities todetect time trends are limited. For herring the number of years required to detect an annualchange of 5 % varies between 13 to 26 years. The power to detect an annual change of 5 %range from 0.08 to 0.36.


Significantly lower nickel concentrations were observed in herring liver from Väderöarnacompared to the samples from Landsort and Karlskrona archipelago.

Mussels from all three sites show mean levels below the upper limit of the ‘highbackground concentration at diffuse loading’ in blue mussels for nickel of <5 g/g dryweight, proposed by Knutzen and Skie (1992).

73

Table 14.1. Geometric mean concentrations of nickel (g/g dry weight) in various matrices and sites duringthe time period and the estimated mean concentration for the last year. The age interval for fish, and the lengthinterval for blue mussels are also presented together with the total number of analyses and the number of yearsof the various time-series.

Matrix age n n yrs year trend % (95% ci) last year(95% ci)Herring liverHarufj. autumn 3-4 124 9 95-03 .15 (.087-.26)Ängskärskl. aut. 3-5 122 9 95-03 -11 (-22, 0.7) .11 (.066-.20)

” spring 3-6 80 8 96-03 -8.8 (-19, 1.7) .20 (.13-.31)Landsort 3-5 123 9 95-03 -11 (-19,-3.5)* .14 (.095-.20)Utlängan, aut. 3-4 110 9 95-03 .31 (.26-.36)

” spring 0-4 70 7 96-03 -8.5 (-18, .97) .22 (.16-.31)Fladen 2-3 121 9 95-03 -20 (-32,-7.9)* .061 (.035-.11)Väderöarna 2-4 180 9 95-03 -14 (-20,-7.9)* .05 (.037-.066)

Cod liverSE Gotland 0-6 110 9 95-03 -8.8 (-16,-2)* .065 (.047-.090)Fladen 0-5 110 9 95-03 -9.5 (-19,-.07)* .12 (.077-.19)

Perch liverHolmöarna 4-7 76 8 95-03 -20 (-48,-1.5)* .045 (.018-.11)Kvädöfjärden 3-6 79 8 95-03 -16 (-36, 3.9) .054 (.020-.15)

Eelpout liverHolmöarna 3-6 19 7 95-03 .19 (.10-.34)Kvädöfjärden 2-6 66 9 95-03 -16 (-25,-7.2)* .11 (.072-.17)Väderöarna 3-5 71 8 95-03 -16 (-26,-5.1)* .14 (.086-.22)

Blue mussel shell lKvädöfjärden 88 9 95-03 2.8 (2.4-3.2)Fladen 139 9 95-03 2.2 (1.8-2.6)Väderöarna 130 9 95-03 1.1 (.91-1.4)

Guillemot eggSt. Karlsö 80 8 96-03 .076 (.048-.12)

significant trend, p < 0.05

Ni, ug/g dry w., herring liver

Harufjarden (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=124,n(yrs)=9m=.149 (.087,.255)slope=-14%(-33,5.9)SD(lr)=33.4,31%,26 yrpower=.08/.09/25%y(03)=.087 (.034,.219)r2=.28, NStao=-.44, p<.095SD(sm)=34.3, NS,26%

Angskarsklubb (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=122,n(yrs)=9m=.175 (.123,.249)slope=-11%(-22,.70)SD(lr)=21.6,17%,19 yrpower=.13/.17/14%y(03)=.114 (.066,.196)r2=.41, p<.060tao=-.39, NSSD(sm)=20.4, NS,13%

Landsort (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=123,n(yrs)=9m=.217 (.161,.293)slope=-11%(-19,-3.5)SD(lr)=16.7,11%,15 yrpower=.24/.32/9.3%y(03)=.138 (.095,.200)r2=.63, p<.011 *tao=-.50, p<.061SD(sm)=16.4, NS,9.2%

Utlangan (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=110,n(yrs)=9m=.307 (.260,.362)slope=-3.4%(-9.8,3.0)SD(lr)=17.7,9.2%,13 yrpower=.34/.46/7.6%y(03)=.268 (.198,.363)r2=.18, NStao=-.33, NSSD(sm)=12.8, p<.051,5.5%

pia - 08.03.19 10:19, NIC

74

Ni, ug/g dry weight, herring liver


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=3-6n(tot)=80,n(yrs)=8m=.271 (.205,.359)slope=-8.8%(-19,1.7)SD(lr)=21.2,15%,16 yrpower=.16/.28/10%y(03)=.199 (.129,.309)r2=.41, p<.083tao=-.50, p<.083

Karlskrona, spring

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=0-4n(tot)=70,n(yrs)=7m=.286 (.226,.363)slope=-8.5%(-18,.97)SD(lr)=15.6,14%,13 yrpower=.19/.51/7.1%y(02)=.222 (.158,.312)r2=.52, p<.068tao=-.71, p<.024 *

Fladen (2-3)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=121,n(yrs)=9m=.134 (.081,.222)slope=-20%(-32,-7.9)SD(lr)=19.4,18%,19 yrpower=.13/.16/15%y(03)=.061 (.035,.107)r2=.69, p<.006 *tao=-.83, p<.002 *

Vaderoarna

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=2-4n(tot)=180,n(yrs)=9m=.087 (.063,.121)slope=-14%(-20,-7.9)SD(lr)=8.19,8.8%,13 yrpower=.36/.49/7.3%y(03)=.050 (.037,.066)r2=.81, p<.001 *tao=-.78, p<.004 *

pia - 08.03.27 09:30, NIV

Ni, ug/g dry w., cod liver

SE Gotland

age=0-6n(tot)=110,n(yrs)=9

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

m=.092 (.072,.118)slope=-8.8%(-16,-2.0)SD(lr)=9.42,9.9%,14 yrpower=.30/.40/8.2%y(03)=.065 (.047,.090)r2=.57, p<.018 *tao=-.50, p<.061

Fladen


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

m=.176 (.131,.237)slope=-9.5%(-19,-.07)SD(lr)=17.7,14%,17 yrpower=.18/.24/11%y(03)=.121 (.077,.188)r2=.45, p<.048 *tao=-.61, p<.022 *

pia - 08.03.19 10:34, nig

75

Ni, ug/g dry w., perch liver

Holmoarna (4-7)

n(tot)=76,n(yrs)=8

.0

.1

.2

.3

.4

.5

.6

.7

.8

94 96 98 00 02 04 06

m=.104 (.055,.196)slope=-20%(-38,-1.5)SD(lr)=24.7,33%,24 yrpower=.07/.10/22%y(03)=.045 (.018,.112)r2=.54, p<.038 *tao=-.57, p<.048 *SD(sm)=11.4, p<.005,9.5%

Kvadofjarden (3-6)

.0

.1

.2

.3

.4

.5

.6

.7

.8

94 96 98 00 02 04 06

n(tot)=79,n(yrs)=8m=.106 (.058,.192)slope=-16%(-36,3.9)SD(lr)=26.7,36%,25 yrpower=.07/.10/23%y(03)=.054 (.020,.145)r2=.39, p<.096tao=-.29, NSSD(sm)=8.97, p<.001,7.3%

pia - 08.03.19 10:39, nip

Ni, ug/g dry w., eelpout liver

Holmoarna (3-6)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=19,n(yrs)=7m=.186 (.103,.338)slope=2.5%(-25,30)SD(lr)=41.8,59%,28 yrpower=.06/.08/28%y(03)=.202 (.065,.625)r2=.01, NStao=.24, NSSD(sm)=35.7, NS,23%

Kvadofjarden (2-6)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=66,n(yrs)=9m=.213 (.142,.320)slope=-16%(-25,-7.2)SD(lr)=19.4,13%,16 yrpower=.19/.25/11%y(03)=.111 (.072,.172)r2=.72, p<.004 *tao=-.78, p<.004 *SD(sm)=18.0, NS,10%

Vaderoarna (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=71,n(yrs)=8m=.248 (.160,.387)slope=-16%(-26,-5.1)SD(lr)=23.0,18%,17 yrpower=.13/.22/12%y(03)=.138 (.086,.224)r2=.69, p<.011 *tao=-.86, p<.003 *SD(sm)=18.8, NS,9.6%

pia - 08.03.19 10:46, NIZ

76

15 ChromiumUpdated 08.03.28


The concentration of chromium in fish liver is determined using an atomic absorptionspectrophotometer with graphite furnace at the Department of Environmental Assessment atSwedish University of Agricultural Sciences. The detection limit is estimated toapproximately 0.1 g/g dry weight.

The analysis started on samples collected 1995.


Chromium decrease significantly in herring from Ängskärsklubb (autumn), Utlängan(autumn), Karlskona (spring), Fladen and Väderöarna, in cod and blue mussels fromFladen, in perch from Holmöarna and in guillemot eggs.

The required minimum years to detect an annual change of 5 % varies between 10 and 33years for herring. The power to detect an annual change of 5 % ranges between 0.06 and0.64.


The chromium concentration in blue mussel samples from the Kattegatt varies betweenyears and shows a geometric mean concentration in the same range as mussels from theBaltic Proper. These concentrations are about 2-3 times higher compared to samples fromthe Skagerack and close to or above the ‘high background concentration at diffuse loading’in blue mussels for chromium of <3 g/g dry weight, proposed by Knutzen and Skie (1992).The samples from the Skagerack are well below this value.

77

Table 15.1. Geometric mean concentrations of chromium (g/g dry weight) in various matrices and sitesduring the time period and the estimated mean concentration for the last year. The age interval for fish, and thelength interval for blue mussels are also presented together with the total number of analyses and the numberof years of the various time-series.

Matrix age n n yrs year trend % (95% ci) last year (95% ci)Herring liverHarufj. autumn 3-4 124 9 95-03 -11 (-22, .42) .18 (.10-.30)Ängskärskl.aut. 3-5 122 9 95-03 -18 (-34,-2.6)* .11 (.049-.22)

” spring 3-6 80 8 96-03 -4.7 (-9.5, .23) .29 (.24-.36)Landsort 3-5 122 9 95-03 .21 (.17-.24)Utlängan, aut. 3-4 110 9 95-03 -24 (-48,-1.1)* .079 (.026-.24)

” spring 0-4 70 7 96-03 -12 (-24,-.57)* .21 (.14-.32)Fladen 2-3 121 9 95-03 -26 (-49,-2.8)* .072 (.024-.22)Väderöarna 2-4 180 9 95-03 -5.5 (-9.8,-1.2)* .21 (.17-.25)

Cod liverSE Gotland 3-4 107 9 95-03 .08 (.039-.16)Fladen 2-4 106 9 95-03 -18 (-39, 2.4) .067 (.025-.18)

Perch liverHolmöarna 90 9 95-03 -8.9 (-15,-2.9)* .10 (.077-.14)Kvädöfjärden 3-6 79 8 95-03 .15 (.067-.33)

Eelpout liverHolmöarna 5-9 53 7 95-03 .27 (.12-.64)Kvädöfjärden 2-6 56 8 95-03 .41 (.37-.46)Väderöarna 3-5 71 8 95-03 .36 (.25-.51)

Blue mussel shell lKvädöfjärden 88 9 95-03 2.3 (1.7-2.7)Fladen 139 9 95-03 -24 (-37,-12)* .82 (.46-1.5)Väderöarna 130 9 95-03 .89 (.73-1.1)

Guillemot eggSt. Karlsö 80 8 95-03 -18 (-23,-13) .12 (.097-.15)


Cr, ug/g dry w., herring liver

Harufjarden (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=124,n(yrs)=9m=.279 (.255,.304)slope=-11%(-22,.42)SD(lr)=27.5,16%,18 yrpower=.14/.18/14%y(03)=.175 (.103,.296)r2=.42, p<.056tao=-.50, p<.061

Angskarsklubb (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06


Landsort (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=122,n(yrs)=9m=.206 (.174,.244)slope=-18%(-47,10)SD(lr)=56.8,48%,33 yrpower=.06/.07/39%y(03)=.093 (.024,.363)r2=.24, NStao=-.17, NS

Utlangan (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06


pia - 08.03.19 10:57, CRC

78

Cr, ug/g dry weight, herring liver

Angskarsklubb,spring

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=3-6n(tot)=80,n(yrs)=8m=.341 (.297,.391)slope=-4.7%(-9.5,.23)SD(lr)=12.0,6.9%,10 yrpower=.53/.86/4.7%y(03)=.289 (.236,.355)r2=.48, p<.057tao=-.50, p<.083

Karlskrona, spring

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=0-4n(tot)=70,n(yrs)=7m=.300 (.218,.412)slope=-12%(-24,-.57)SD(lr)=19.9,17%,14 yrpower=.14/.36/8.8%y(02)=.208 (.136,.316)r2=.59, p<.043 *tao=-.62, p<.051

Fladen (2-3)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06


Vaderoarna

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

age=2-4n(tot)=180,n(yrs)=9m=.258 (.221,.301)slope=-5.5%(-9.8,-1.2)SD(lr)=10.4,6.1%,11 yrpower=.64/.79/5.1%y(03)=.207 (.168,.254)r2=.57, p<.019 *tao=-.56, p<.037 *

pia - 08.03.27 09:28, CRV

Cr, ug/g wet w., blue mussel softbodyShell lengths in brackets

Fladen (5-8 cm)

n(tot)=136,n(yrs)=9

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

94 96 98 00 02 04 06

m=.302 (.172,.529)slope=-22%(-35,-9.5)SD(lr)=35.2,19%,20 yrpower=.12/.15/16%y(03)=.123 (.067,.228)r2=.71, p<.005 *tao=-.61, p<.022 *SD(sm)=38.9, NS,18%

Vaderoarna (6-10)

n(tot)=130,n(yrs)=9

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

94 96 98 00 02 04 06

m=.155 (.128,.187)slope=1.3%(-6.6,9.2)SD(lr)=13.9,12%,15 yrpower=.24/.32/9.5%y(03)=.163 (.112,.237)r2=.02, NStao=.06, NSSD(sm)=10.5, p<.064,7.1%

Kvadofjarden

length=0-3n(tot)=88,n(yrs)=9

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

94 96 98 00 02 04 06

m=.284 (.263,.306)slope=-3.5%(-6.3,-.67)SD(lr)=27.1,.50%,18 yrpower=1.0/.20/13%y(03)=.247 (.217,.282)r2=.07, p<.015 *tao=-.22, p<.002 *

pia - 08.03.19 11:16, CRWM

79

16 CopperUpdated 08.03.28


The concentration of copper in fish liver is determined using an atomic absorptionspectrophotometer with graphite furnace at the Department of Environmental Assessment atSwedish University of Agricultural Sciences.

Copper is a nutritionally essential metal and the concentration is regulated by homeostaticmechanisms. The free copper is effectively controlled by metallothionein synthesis (daSilva and Williams, 1994) induced by copper it self or by other substances. Althoughcopper is not believed to accumulate with continued exposure, changes found in biologicaltissues may still reflect changes in concentration of the ambient water.

The copper concentration in liver from Baltic herring is about 4.5 times higher than theconcentration reported from the edible parts of herring. For cod the concentration in theliver is about 40-60 times higher and for perch about 12-14 times. Concentrations in edibleparts are reported by Jorhem and Sundström, 1993.

The concentration of copper in fish liver and blue mussel soft body is determined using anatomic absorption spectrophotometer with graphite furnace. The detection limit is estimatedto approximately 10 ng/g dry weight.



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the copper discharges are to be reduced by 50% between 1985 and1995, using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of thedischarges of copper to air and water by 50% by 1995 with 1987 as a base year.


A significant upward trend of copper in herring was found at Utlängan and significantlydecreasing trends at Fladen for herring and blue mussels.

The number of years required to detect an annual change of 5% varied between 12 to 15years for the herring time series at a power of 80%.

80


No significant differences in mean copper concentration in herring between the samplingsites were found.

The copper concentration in blue mussels from the Swedish west coast is not significantlydifferent compared to blue mussel samples of similar length from a reference site atKobbefjord, Greenland (Riget et al 1993). Mussel samples from all three sites show meanlevels below the ‘high background concentration at diffuse loading’ in blue mussels forcopper of <10 g/g dry weight, proposed by Knutzen and Skie (1992).


Significant differences in mean copper concentration, in fish liver and blue mussel softbody, were found between the species marked with '>':

Kvädöfjärden: Eelpout(22) > Perch(13) > Blue mussel (7.9)Fladen: Cod(17) > Herring(10) > Blue mussel(5.4)Väderöarna: Eelpout(31) > Herring(9.2) > Blue mussel(5.2)

81

Table 16.1. Geometric mean concentrations of copper (g/g dry weight) in various matrices and sites duringthe time period and the estimated mean concentration for the last year. The age interval for fish, and the lengthinterval for blue mussels are also presented together with the total number of analyses and the number of yearsof the various time-series.

Matrix age n n yrs year trend last yearHerring liver

Harufj. autumn 3-4 363 22 81-03 11 (9.6-12)Ängskärskl. aut. 3-5 383 22 81-03 1.6 (.35, 2.9) 13 (11-16)

” spring 80 8 96-03 13 (11-15)Landsort 3-5 370 23 81-03 12 (10-13)Utlängan, aut. 3-4 287 23 81-03 1.4 (.00, 2.8)* 14 (12-17)

” spring 69 7 96-03 14 (10-18)Fladen 2-3 443 23 81-03 -1.5 (-3.2, 0.13) 10 (8.4-13)Väderöarna 180 9 95-03 9.2 (8.4-10)

Cod liverSE Gotland 3-4 343 23 81-03 16 (15-18)Fladen 2-4 425 23 81-03 17 (14-21)

Perch liverHolmöarna 0-7 90 9 95-03 11 (8.6-13)Kvädöfjärden 3-7 80 8 95-03 13 (10-15)

Eelpout liverHolmöarna 3-* 67 7 95-03 12 (10-13)Kvädöfjärden 2-9 89 9 95-03 22 (20-25)Väderöarna 3-8 79 8 95-03 31 (28-35)

Dab liverFladen 3-5 257 14 81-94 18 (14-23)

Flounder liverVäderöarna 4-6 239 14 81-94 51 (35-74)

Blue mussel sh. lFladen 5-8 396 21 81-03 -1.1 (-2.2, .03) 5.4 (4.7-6.2)Väderöarna 6-10 413 22 81-03 5.2 (4.9-5.6)Kvädöfjärden 88 9 95-03 7.9 (7.2-8.7)

Guillemot eggSt. Karlsö 80 8 96-03 2.9 (2.7-3.2)


Cu, ug/g dry w., herring liver

Harufjarden (3-4)

0

5

10

15

20

25

30

35

40

45

80 85 90 95 00 05

n(tot)=363,n(yrs)=22m=10.8 ( 9.6,12.0)slope=-.43%(-2.1,1.2)SD(lr)=10.7,2.6%,15 yrpower=1.0/.33/9.3%y(03)=10.3 ( 8.3,12.7)r2=.01, NStao=-.03, NSSD(sm)=9.29, NS,8.0%slope=-.03%(-6.2,6.2)SD(lr)=10.7,8.9%,14 yrpower=.35/.35/8.9%r2=.00, NS

Angskarsklubb (3-5)

0

5

10

15

20

25

30

35

40

45

80 85 90 95 00 05

n(tot)=383,n(yrs)=22m=11.1 (10.1,12.2)slope=1.6%(.35,2.9)SD(lr)=7.88,1.9%,12 yrpower=1.0/.53/6.9%y(03)=13.2 (11.3,15.5)r2=.26, p<.014 *tao=.26, p<.085SD(sm)=7.84, NS,6.8%slope=2.7%(-2.7,8.1)SD(lr)=8.59,7.7%,13 yrpower=.44/.44/7.7%r2=.14, NS

Landsort (3-5)

0

5

10

15

20

25

30

35

40

45

80 85 90 95 00 05

n(tot)=370,n(yrs)=23m=11.7 (10.4,13.1)slope=.26%(-1.5,2.0)SD(lr)=10.8,2.5%,15 yrpower=1.0/.30/9.8%y(03)=12.0 ( 9.6,15.0)r2=.00, NStao=-.03, NSSD(sm)=5.26, p<.001,4.7%slope=-6.4%(-9.6,-3.1)SD(lr)=5.22,4.6%,10 yrpower=.87/.87/4.6%r2=.72, p<.002 *

Utlangan (3-4)

0

5

10

15

20

25

30

35

40

45

80 85 90 95 00 05

n(tot)=287,n(yrs)=23m=12.3 (11.1,13.6)slope=1.4%(.00,2.8)SD(lr)=8.66,2.0%,14 yrpower=1.0/.43/7.9%y(03)=14.4 (12.0,17.3)r2=.17, p<.047 *tao=.36, p<.016 *SD(sm)=9.12, NS,8.3%slope=.95%(-3.4,5.3)SD(lr)=6.76,6.2%,12 yrpower=.62/.62/6.2%r2=.03, NS

pia - 08.03.19 13:19, CUC

82

Cu, ug/g dry w., herring (liver)

Angskarskl., spring

0

5

10

15

20

25

30

35

40

45

96 98 00 02 04 06

n(tot)=80,n(yrs)=8m=13.1 (11.4,15.1)slope=-2.4%(-8.7,4.0)SD(lr)=6.55,9.1%,12 yrpower=.34/.64/6.1%y(03)=12.1 ( 9.3,15.8)r2=.12, NStao=.07, NSSD(sm)=5.97, NS,5.5%slope=-2.4%(-8.7,4.0)SD(lr)=6.55,9.1%,12 yrpower=.34/.64/6.1%r2=.12, NS

Karlskrona, spring

0

5

10

15

20

25

30

35

40

45

96 98 00 02 04 06

n(tot)=69,n(yrs)=7m=13.6 (10.3,17.8)slope=-8.2%(-21,4.3)SD(lr)= 9.8,18%,15 yrpower=.13/.32/9.4%y(02)=10.6 ( 6.8,16.6)r2=.36, NStao=-.43, NSSD(sm)=6.15, p<.024,5.8%slope=-8.2%(-21,4.3)SD(lr)= 9.8,18%,15 yrpower=.13/.32/9.4%r2=.36, NS

Fladen (2-3)

0

5

10

15

20

25

30

35

40

45

80 85 90 95 00

n(tot)=443,n(yrs)=23m=12.3 (10.9,13.8)slope=-1.5%(-3.2,.13)SD(lr)=10.2,2.4%,15 yrpower=1.0/.32/9.3%y(03)=10.4 ( 8.4,12.8)r2=.15, p<.066tao=-.29, p<.054SD(sm)=8.18, p<.043,7.4%slope=.64%(-2.7,3.9)SD(lr)=5.53,4.7%,10 yrpower=.86/.86/4.7%r2=.02, NS

Vaderoarna

0

5

10

15

20

25

30

35

40

45

94 96 98 00 02 04

n(tot)=180,n(yrs)=9m=9.17 (8.42,10.0)slope=-1.1%(-4.6,2.3)SD(lr)=5.10,4.9%,9 yrpower=.83/.94/4.1%y(03)= 8.8 ( 7.4,10.3)r2=.08, NStao=-.17, NSSD(sm)=4.39, NS,3.5%slope=-1.1%(-4.6,2.3)SD(lr)=5.10,4.9%,9 yrpower=.83/.94/4.1%r2=.08, NS

pia - 08.03.27 09:28, cuv

Cu, ug/g dry w., perch liver

Holmoarna


0

5

10

15

20

25

30

35

40

45

94 96 98 00 02 04

m=10.6 (8.63,13.0)slope=-4.5%(-12,3.4)SD(lr)=10.8,11%,15 yrpower=.24/.32/9.4%y(03)= 8.9 ( 6.1,12.9)r2=.21, NStao=-.39, NS

Kvadofjarden


0

5

10

15

20

25

30

35

40

45

94 96 98 00 02 04

m=12.5 (10.3,15.2)slope=-3.6%(-11,3.8)SD(lr)=8.99,12%,14 yrpower=.21/.40/8.3%y(03)=10.7 ( 7.4,15.6)r2=.19, NStao=-.21, NS

pia - 08.03.19 15:53, CUP

83

Cu, ug/g wet w., blue mussel softbodyShell lengths in brackets

Fladen (5-8 cm)

.0

.5

1.0

1.5

2.0

2.5

3.0

80 85 90 95 00 05

n(tot)=396,n(yrs)=21m=.903 (.799,1.02)slope=-2.8%(-4.1,-1.5)SD(lr)=187 ,2.1%,13 yrpower=1.0/.53/6.9%y(03)=.674 (.573,.793)r2=.51, p<.001 *tao=-.57, p<.001 *SD(sm)=175 , NS,6.5%slope=-3.3%(-8.4,1.8)SD(lr)=85.6,7.3%,13 yrpower=.49/.49/7.3%r2=.22, NS

Vaderoarna (6-10)

.0

.5

1.0

1.5

2.0

2.5

3.0

80 85 90 95 00 05

n(tot)=413,n(yrs)=22m=.915 (.823,1.02)slope=-1.1%(-2.6,.44)SD(lr)=258 ,2.3%,14 yrpower=1.0/.39/8.4%y(03)=.812 (.668,.988)r2=.10, NStao=-.22, NSSD(sm)=192 , p<.017,6.2%slope=-5.9%(-12,-.08)SD(lr)=183 ,8.3%,14 yrpower=.39/.39/8.3%r2=.41, p<.046 *

Kvadofjarden

.0

.5

1.0

1.5

2.0

2.5

3.0

94 96 98 00 02 04 06

n(tot)=88,n(yrs)=9m=1.02 (.923,1.12)slope=.69%(-3.3,4.7)SD(lr)=869 ,5.7%,10 yrpower=.70/.85/4.7%y(03)=1.04 ( .86,1.26)r2=.02, NStao=.11, NSSD(sm)=653 , p<.063,3.5%slope=.69%(-3.3,4.7)SD(lr)=869 ,5.7%,10 yrpower=.70/.85/4.7%r2=.02, NS

pia - 08.03.19 16:03, CUWM


84

17 ZincUpdated 08.03.28


The time series of zinc concentration in fish liver and blue mussel soft body, presentedbelow, start 1981. It is determined using an atomic absorption spectrophotometer withgraphite furnace at the Department of Environmental Assessment at Swedish University ofAgricultural Sciences

Zinc is a nutritionally essential metal and the concentration is regulated by homeostaticmechanisms. Hence, zinc is not believed to accumulate with continued exposure butchanges found in biological tissues may still reflect changes in concentration of the ambientwater.

The zinc concentration in liver from Baltic herring is about 1.5 times higher than theconcentration reported from the edible parts of herring. For cod the concentration in theliver is about 6 - 8 times higher and for perch about 3.5 times. Concentrations in edibleparts are reported by Jorhem and Sundström, 1993.

The concentration of zinc in fish liver and blue mussel soft body is determined using anatomic absorption spectrophotometer with graphite furnace. The detection limit is estimatedto approximately 100 ng/g dry weight.



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the zinc discharges are to be reduced by 50% between 1985 and 1995,using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of thedischarges of zinc to air and water by 50% by 1995 with 1987 as a base year.


Significant downward trends are shown in herring liver from Landsort (the past ten years)and in guillemot eggs during the whole analysed time period. Significant upward trends arefound for herring from Harufjärden and Fladen for the whole period and also for Utlänganthe last ten years.

The number of years required to detect an annual change of 5% varied between 9 to 13years for the herring time series with a power to detect a 5% annual change ranging from

85

0.43 for the shorter time series to 1.0 for the longer ones. (Since it is not appropriate to fit alog-linear trend at Harufjärden and Utlängan, these sites were excluded from the powercalculations.)


No significant differences in mean zinc concentration are observed in herring among thesampling sites in the Baltic Sea and the Swedish west coast.

The zinc concentration in cod liver from Fladen is significantly higher than in cod liverfrom the site SE of Gotland. This may be explained by the significantly lower fat content incod liver from Fladen since zinc concentration is negatively correlated with fat content.

The zinc concentration in blue mussels from the Swedish west coast is not significantlydifferent compared to blue mussel samples of similar length from a reference site atKobbefjord, Greenland (Riget et. al 1993). The zinc concentrations in blue mussels from allthe three investigated sites are below the proposed background concentrations for the NorthSea (ICES, 1997)

17.3 Differences among various species

Significant differences in mean zinc concentration, in fish liver and blue mussel soft body,were found between the species marked with '>':

Holmöarna: Eelpout(158) > Perch(102)Kvädöfjärden: Eelpout(189) > Perch(114)Fladen: Blue mussel(112) - Herring(105) > Cod(71)Väderöarna: Blue mussel (108) - Herring(107)


The concentrations in spring caught herring from Ängskärsklubb and Utlängan isconsiderable higher compared to samples from the same areas in the autumn (table 17.1).

86

Table 17.1. Geometric mean concentrations of zinc (g/g dry weight) in various matrices and sites during thetime period and the estimated mean concentration for the last year. The age interval for fish, and the lengthinterval for blue mussels are also presented together with the total number of analyses and the number of yearsof the various time-series.

Matrix age n nyrs

year trend (95% ci) last year

Herring liverHarufj. autumn 3-4 344 21 81-03 1.6 (.22, 3.0)* 110 (96-140)Ängskärskl. aut. 3-5 363 21 81-03 100 (94-110)

” spring 3-6 80 8 96-03 150 (130-170)Landsort 3-5 352 22 81-03 93 (87-100)Utlängan, aut. 3-4 270 22 81-03 100 (94-110)

” spring 0-4 70 7 96-03 130 (100-150)Fladen 418 22 81-03 1.0 (.25, 1.8)* 110 (95-120)Väderöarna 2-4 180 9 95-03 110 (94-120)

Cod liverSE Gotland 3-4 325 22 81-03 34 (30-39)Fladen 2-4 403 22 81-03 71 (66-77)

Perch liverHolmöarna 0-7 90 9 95-03 100 (90-120)Kvädöfjärden 3-7 80 8 95-03 110 (92-140)

Eelpout liverHolmöarna 67 7 95-03 160 (130-190)Kvädöfjärden 2-9 89 9 95-03 190 (150-240)Väderöarna 3-8 79 8 95-03 220 (180-270)

Dab liverFladen 3-5 234 13 81-94 88 (77-101)

Flounder liverVäderöarna 4-6 232 13 81-94 183 (149-223)

Blue mussel sh. lFladen 5-8 396 21 81-03 110 (100-130)Väderöarna 6-10 391 21 81-03 110 (94-120)Kvädöfjärden 88 9 95-03 130 (120-150)

Guillemot eggSt. Karlsö 80 8 96-03 -2.8 (-5.3,-.33)* 43 (38-47)

NL = non-linear trend components


87

Zn, ug/g dry w., herring liver

Harufjarden (3-4)

0

20

40

60

80

100

120

140

160

180

200

220

240

260

80 85 90 95 00 05

n(tot)=344,n(yrs)=21m=95.9 (86.6,106 )slope=1.6%(.22,3.0)SD(lr)=4.43,2.2%,13 yrpower=1.0/.48/7.3%y(03)= 113 ( 96, 135)r2=.24, p<.024 *tao=.39, p<.013 *SD(sm)=3.11, p<.012,5.1%slope=3.6%(-1.2,8.4)SD(lr)=4.10,6.9%,13 yrpower=.53/.53/6.9%r2=.27, NS

Angskarsklubb (3-5)

0

20

40

60

80

100

120

140

160

180

200

220

240

260

80 85 90 95 00 05

n(tot)=363,n(yrs)=21m=101 (94.1,108 )slope=.79%(-.24,1.8)SD(lr)=3.26,1.6%,11 yrpower=1.0/.74/5.4%y(03)= 110 ( 97, 125)r2=.12, NStao=.24, NSSD(sm)=3.46, NS,5.8%slope=1.8%(-3.2,6.9)SD(lr)=4.29,7.3%,13 yrpower=.49/.49/7.3%r2=.08, NS

Landsort (3-5)

0

20

40

60

80

100

120

140

160

180

200

220

240

260

80 85 90 95 00 05

n(tot)=352,n(yrs)=22m=93.2 (87.0,100 )slope=-.22%(-1.3,.85)SD(lr)=3.51,1.6%,11 yrpower=1.0/.69/5.8%y(03)= 91 ( 80, 104)r2=.01, NStao=-.13, NSSD(sm)=2.85, p<.056,4.6%slope=-2.8%(-5.7,.18)SD(lr)=2.58,4.2%,9 yrpower=.93/.93/4.2%r2=.37, p<.060

Utlangan (3-4)

0

20

40

60

80

100

120

140

160

180

200

220

240

260

80 85 90 95 00 05

n(tot)=270,n(yrs)=22m=100 (94.2,106 )slope=.59%(-.27,1.4)SD(lr)=2.77,1.3%,10 yrpower=1.0/.87/4.6%y(03)= 106 ( 95, 118)r2=.09, NStao=.18, NSSD(sm)=2.04, p<.018,3.4%slope=3.5%(.56,6.4)SD(lr)=2.47,4.1%,9 yrpower=.93/.93/4.1%r2=.49, p<.025 *

pia - 08.03.19 14:04, ZNC

Zn, ug/g dry weight, herring liver


0

20

40

60

80

100

120

140

160

180

200

220

240

260

280

96 98 00 02 04 06

age=3-6n(tot)=80,n(yrs)=8m=146 (129 ,165 )slope=-2.0%(-7.6,3.6)SD(lr)=2.96,7.9%,11 yrpower=.43/.76/5.3%y(03)= 136 ( 108, 172)r2=.11, NStao=-.29, NS

Karlskrona, spring

0

20

40

60

80

100

120

140

160

180

200

220

240

260

280

96 98 00 02 04 06

age=0-4n(tot)=70,n(yrs)=7m=125 (102 ,153 )slope=-4.2%(-15,6.3)SD(lr)=4.48,15%,13 yrpower=.16/.43/7.9%y(02)= 110 ( 75, 161)r2=.18, NStao=-.05, NS

Fladen (2-3)

0

20

40

60

80

100

120

140

160

180

200

220

240

260

280

80 85 90 95 00 05

n(tot)=418,n(yrs)=22m=93.9 (88.5,100 )slope=1.0%(.25,1.8)SD(lr)=2.53,1.2%,9 yrpower=1.0/.93/4.1%y(03)= 105 ( 95, 115)r2=.27, p<.012 *tao=.42, p<.006 *SD(sm)=2.44, NS,4.0%slope=.92%(-2.7,4.5)SD(lr)=3.06,5.1%,11 yrpower=.80/.80/5.1%r2=.04, NS

Vaderoarna

0

20

40

60

80

100

120

140

160

180

200

220

240

260

280

94 96 98 00 02 04 06

age=2-4n(tot)=180,n(yrs)=9m=107 (94.3,121 )slope=-1.8%(-6.9,3.2)SD(lr)=3.54,7.2%,12 yrpower=.50/.66/6.0%y(03)= 99 ( 78, 126)r2=.09, NStao=-.22, NS

pia - 08.03.27 09:31, ZNV

88

Zn, ug/g dry w., cod liverFat adjusted geometric means

SE Gotland (3-4)

0

20

40

60

80

100

120

140

160

80 85 90 95 00 05

n(tot)=325,n(yrs)=22m=34.4 (30.4,38.9)slope=.48%(-1.4,2.4)SD(lr)=8.06,2.9%,16 yrpower=1.0/.27/11%y(03)=36.2 (28.4,46.0)r2=.01, NStao=.04, NSSD(sm)=7.97, NS,10%

slope=-3.8%(-14,6.1)SD(lr)=10.8,15%,19 yrpower=.16/.16/15%r2=.09, NS

Fladen (2-4)

0

20

40

60

80

100

120

140

160

80 85 90 95 00 05

n(tot)=403,n(yrs)=22m=70.8 (65.5,76.5)slope=-.27%(-1.5,.93)SD(lr)=4.19,1.8%,12 yrpower=1.0/.59/6.5%y(03)=68.7 (59.1,79.9)r2=.01, NStao=.12, NSSD(sm)=4.30, NS,6.6%

slope=.75%(-3.0,4.5)SD(lr)=3.47,5.3%,11 yrpower=.76/.76/5.3%r2=.03, NS

pia - 08.03.19 14:35, ZNG

Zn, ug/g wet w., blue mussel softbodyShell lengths in brackets

Fladen (5-8 cm)

0

5

10

15

20

25

30

35

40

45

50

55

80 85 90 95 00 05

n(tot)=396,n(yrs)=21m=16.9 (15.2,18.6)slope=-.85%(-2.4,.67)SD(lr)=7.79,2.4%,14 yrpower=1.0/.42/8.0%y(03)=15.4 (12.8,18.6)r2=.07, NStao=-.07, NSSD(sm)=6.83, NS,7.0%slope=-2.8%(-9.3,3.6)SD(lr)=9.18,9.3%,15 yrpower=.33/.33/9.3%r2=.11, NS

Vaderoarna (6-10 cm)

0

5

10

15

20

25

30

35

40

45

50

55

80 85 90 95 00 05

n(tot)=391,n(yrs)=21m=17.3 (15.0,20.0)slope=.61%(-1.6,2.8)SD(lr)=11.3,3.5%,17 yrpower=.99/.22/12%y(03)=18.5 (14.1,24.4)r2=.02, NStao=.03, NSSD(sm)=9.10, p<.057,9.5%slope=-6.8%(-13,-.36)SD(lr)=8.63,9.3%,15 yrpower=.33/.33/9.3%r2=.43, p<.040 *

Kvadofjarden

0

5

10

15

20

25

30

35

40

45

50

55

94 96 98 00 02 04 06

n(tot)=88,n(yrs)=9m=16.9 (14.4,19.9)slope=-1.6%(-8.4,5.2)SD(lr)=7.89,9.8%,14 yrpower=.30/.41/8.1%y(03)=15.8 (11.5,21.9)r2=.04, NStao=.00, NSSD(sm)=6.65, NS,6.8%slope=-1.6%(-8.4,5.2)SD(lr)=7.89,9.8%,14 yrpower=.30/.41/8.1%r2=.04, NS

pia - 08.03.19 14:54, ZNWM


89

18 PCB's, Polychlorinatedbiphenyles

Updated 09.05.31

PCB’s have been used in a wide variety of manufacturing processes especially asplasticizers and as insulators and fire retardants. It is widely distributed in the environmentthrough inappropriate handling of waste material or e.g. leakage from large condensers andhydraulic systems. Their toxicological effects e.g. on reproduction in mink is welldocumented (Aulerich et al. 1977, Jensen et al. 1977 and Bleavins et al. 1980).

The number of possible congeners is 209, having one to ten chlorines. Twenty of these havenon-ortho chlorine substitutions and so can attain a planar structure similar to the highlytoxic polychlorinated dibenzo-p-dioxins and dibenzofurans (McKinney et al. 1985, Sericoet al. 1991).

Seven CB-congeners (CB-28, CB-52, CB-101, CB-118, CB-138, CB-153 and CB-180) arelisted as mandatory contaminants that should be analysed and reported within both theOSPARCOM and the HELCOM conventions. In the proposed revised guidelines forOSPARCOM (1996) the congeners CB-105 and CB-156 are added to this list.

The concentration of the PCB’s in fish muscle, cod liver, blue mussel soft body andguillemot egg is determined using a gas chromatograph (GC) equipped with an electroncapture detector.

Before 1988, PCB’s were analysed by a packed column GC and the total sum of PCB wasestimated from 14 peaks after calibration with Aroclor 1254 (Jensen et al. 1983). During1988, analyses on capillary column were introduced, admitting analysis of individualcongeners (Eriksson et al., 1994).

Although the relative abundance of the various CB-congeners is considered to be fairlyconstant, both geographical differences and temporal changes in the ratios between theinvestigated congeners can be shown, see below.

Coeluation of congeners in GC analysis is dependent upon instrumental conditions such ascolumn type, length, internal diameter, film thickness and oven temperature etc. Somepotentially coeluting PCB congeners are CB-28/-31, CB-52/-49, CB-101/-90, CB-138/-163/-164 and CB-153/-132/-105 (Schantz et al.,1993). During recent years it has beendiscovered that congener CB-163, and possibly also CB-164, has interfered with CB-138(see also Roos et al. 1990). This implies that the reported concentration of CB-138 alsoincludes a minor contribution from CB-163 and possibly also from CB-164.

The sum of PCB’s (sPCB), presented in this report, is estimated from the concentration ofpeak 10 (PCB10) in the chromatogram from packed column chromatography using theratio, R1=PCB10/sPCB. PCB10 constitute approximately 11-14%, of the total amount ofPCB in herring, 13-15% in cod, 16-17% in perch, 12 % in blue mussel and 18% inguillemot egg. Thus, the ratio varies between matrices but is very stable within the samematrix at the same sampling site - the coefficient of variation is found, with few exceptions,to be between 3.5 - 6%, see CV1 in table 18.1 From 1989 and forward, PCB10concentrations have been estimated using the ratio, R2=(CB-138 + CB-163)/PCB10. CB-138 + CB-163 constitute about 60-80% of PCB10 and 7-12% of the total sum of PCB’s inherring. The mean ratios are given in table 18.1, below.

90

The sum of PCB’s is until 1988 estimated according to:

sPCB = PCB10 / R1

and after 1988:

sPCB = (CB-138+CB-163) /(R1 R2)

Table 18.1. Mean ratios between peak 10 and the total sum of PCB’s, from packed column gaschromatography (GC) (R1) and mean ratios between CB-138+CB-163 (capillary GC) and PCB10 (R2). Alsothe number of analyses (n) and the Coefficient of Variation (CV) for the two ratios are given.

n1 R1 CV1 n2 R2 C.I. CV2 R1 R2

HerringHarufjärden 169 .14 4.0 19 .73 .67-.76 9.1 .098Ängskärsklubb 188 .14 5.1 20 .83 .79-.88 11 .12

” spring 397 .13 5.1 25 .79 .75-.82 11 .10Landsort 159 .12 5.2 29 .61 .59-.63 7.4 .070Utlängan 94 .12 5.4 20 .65 .62-.68 9.8 .075

” spring 371 .12 5.3 10 .67 .64-.69 5.4 .080Fladen 191 .13 5.3 25 .82 .79-.86 10 .11

CodGotland 152 .14 4.0 11 .69 .65-.72 7.3 .093Fladen 176 .15 5.9 10 .85 .81-.89 6.9 .13

PerchHolmöarna 140 .17 5.3Kvädöfjärden 108 .16 6.0

DabFladen 153 .18 5.9 10 .71 18 .13

FlounderVäderöarna 137 .13 9.8 5 .74 11 .096

Blue musselFladen 5 .12 11. 1 .74 - .087Väderöarna 9 .12 5.6 1 .95 - .11

GuillemotSt. Karlsö 211 .18 3.5 30 .77 .74-.80 9.8 .14

Table 18.2. Approximate detection limit (capillary column, GC) for the analysed CB-congeners

Congener ng/g, fat weight

CB-28 (2,4,4’-tri CB) 4CB-52 (2,2’,5,5’-tetra CB) 4CB-101 (2,2’,4,5,5’-penta CB) 4CB-118 (2,3’,4,4’,5-penta CB) 5CB-138 (2,2’,3,4,4’,5-hexa CB) 6CB-153 (2,2’,4,4’,5,5’-hexa CB) 5CB-180 (2,2’,3,4,4’,5,5’-hepta CB 4

91



The Helsinki Convention (HELCOM) revised 1992 especially names PCB for whichspecial bans and restrictions on transport, trade, handling, use and disposal are imposed.The Minister Declaration from 1988, within HELCOM, calls for a reduction of stableorganic substances by 50% by 1995 with 1987 as a base year.

The Minister Declaration from 1996, within HELCOM, and the declaration in Esbjerg1995, calls for measures for toxic, persistent, bioaccumulating substances to have ceasedcompletely in the year 2020.

The use of PCB was banned in Sweden in 1973, except for sealed systems. In 1978, all newuse of PCB was forbidden.


The concentration of sPCB (sum of PCB’s estimated from CB-138 or peak 10 from packedcolumn chromatography) in herring muscle from all herring sites in the Baltic and at thewest coast show significant decreasing trends during the time period 1978/80-2007. Theaverage rate varies between -5 and -10% per year. A similar significant decrease within thesame range (5 and 10% a year) was also found in the two time series of spring caughtherring, 1972-2007. This implies a total decrease of about 70% at Ängskärsklubb and about90% at Karlskrona, of the PCB-concentration in herring muscle, since the beginning of theseventies.

An extremely high concentration of PCB’s was recorded at Landsort 1996. This could mostprobably be explained by the very low fat content in herring this year.

The two cod time series from south east of Gotland in the Baltic Proper and Fladen at thewest coast show significant decreasing trends.

Also in the time series of perch the sPCB concentrations have decreased as well as in bluemussel from the west coast and in guillemot eggs (1969-2007). The latter trend correspondsto a total decrease of almost 90% since the beginning of the seventies.

The number of years required to detect an annual change of 5% varied between 14 to 22years for the herring, perch, musssel and cod time series.

18.1.3 Conclusion

The concentration of PCB has decreased approximately with 5-10% per year, in herring andcod from the Baltic Sea and Kattegatt as well as in guillemot eggs and perch from the BalticSea, since the end of the seventies.

92


CB-153

< 0.05

0.05 - 0.1

> 0.1

ug/g lw

TISS - 09.05.05 13:03, CB-153

Figure 18.1. Spatial variation in concentration (l.w.) of CB-153 in herring muscle. (N.B., the bar in theBothnian Bay represent the site Rånefjärden, Harufjärden shows lower concentrations but is hidden behind)

The figure 18.1 indicates that herring muscle from Ängskärsklubb, Långvindsfjärden andGaviksfjärden in the Bothnian Sea and Lagnö in the Baltic Proper show elevatedconcentrations of CB-153 compared to Harufjärden in the Bothnian Bay and Fladen andVäderöarna (lipid weight). Yet only one year is presentetd for the new sampling sites.

The estimated concentration of CB-153 (wet weight) for year 2007 from Harufjärden in theBothnian Bay show similar, or in fact lower concentrations compared to Fladen in theKattegatt and Väderöarna in the Skagerack, and significantly lower than herring samplesfrom the Bothnian Sea and the Baltic Proper.

The ratio CB-118/CB-153 is significantly lower at Ängskärsklubb compared to all the othersites. Herring from Landsort has the highest ratio.

A significant difference was found between CB-153 (lipid weight) concentrations analysedin cod liver from south east of Gotland (higher) and the Kattegatt (lower).

93

Table 18.3. Geometric mean concentrations of sPCB (g/g lipid weight) in various matrices and sites duringthe time period and the estimated mean concentration for the last year. The age interval for fish, and the lengthinterval for blue mussels are also presented together with the total number of analyses and the number of yearsof the various time-series.

Matrix age n n yrs year trend (95% ci) last year (95% ci)Herring msc.Harufj. autumn 3-4 382 28 78-07 -8.9 (-10,-7.6)* .18 (.14-.23)Ängskärskl. aut. 3-5 353 28 78-07 -7.7 (-8.9,-6.6)* .35 (.29-.43)

” spring 2-5 623 34 72-07 -5.1 (-6.2,-3.9)* 1.1 (0.9-1.4)Landsort 3-5 383 29 78-07 -5.4 (-6.7,-4.2)* .65 (.53-.79)Utlängan, aut. 3-4 291 28 80-07 -5.4 (-6.6,-4.2)* .54 (.44-.65)

” spring 2-4 614 33 72-07 -9.9 (-11,-9.0)* .63 (.53-.75)Fladen 2-3 469 28 80-07 -7.6 (-8.7,-6.5)* .15 (.13-.18)

Cod liverSE Gotland 3-4 304 28 80-07 -6.2 (-7.7,-4.6)* .94 (.74-1.2)Fladen 2-3 322 27 80-07 -6.2 (-8.5,-3.9)* 1.2 (.86-1.8)

Perch muscleHolmöarna 4-7 269 21 80-07 -8.9 (-11,-7.1)* .23 (.18-.31)Kvädöfjärden 3-4 222 24 80-07 -9.40 (-12,-7.0)* .11 (.08-.16)

Dab muscleFladen 3-6 158 13 81-94 -4.6 (-12,2.8) 0.72 (.40-1.3)

Flounder mscVäderöarna 4-6 143 15 80-94 -2.8 (-7.4,1.8) 1.7 (1.2-2.6)

Blue musselFladen 74 21 84-07 -6.9 (-8.8,-5.0)* .22(.17-.28)Väderöarna 75 22 84-07 -7.6 (-9.8,-5.3)* .23 (.17-.32)

Guillemot eggSt. Karlsö 380 36 69-07 -8.9 (-9.4,-8.3)* 13 (12-15)


94

Table 18.4. Geometric mean concentrations of CB-153 (ug/g lipid weight) in various matrices and sitesduring 1987-2007 and estimated mean concentration for the last year.

Matrix age n tot n yrs year trend last yrHerring msc.Harufj. autumn 3-4 266 19 87-07 -4.1 (-7.3,-0.97)* .034 (.025-.048)Ängskärskl. aut. 3-5 287 19 89-07 -5.9 (-8.6,-3.1)* .075 (.056-.10)

” spring 259 19 89-07 .22 (.17-.27)Landsort 3-5 304 21 87-07 -4.7 (-8.0,-1.3)* .067 (.045-.098)Utlängan, aut. 3-4 267 20 88-07 .074 (.053-.10)

” spring 254 19 87-07 -6.0 (-8.4 -3.6)* .10 (.077-.13)Fladen 2-3 324 20 88-07 -6.2 (-8.3,-4.1)* .025 (.019-.031)Väderöarna 231 12 95-07 .019 (.013-.028)Cod liverSE Gotland 3-4 152 19 89-07 -1.8 (-4.0, 0.31) .19 (.16-.21)Fladen 2-3 146 19 89-07 .44 (.36-.53)

Perch muscleHolmöarna 139 14 89,95-07 -11 (-16, -5.6)* .10 (.065-.135)Kvädöfjärden 201 20 84,89-07 -6.8 (-11, -2.8)* .052 (.039-.069)

Eelpout muscleHolmöarna 96 11 95,97-07 .15 (.10-.21)Kvädöfjärden 121 13 95-07 -11 (-17, -5.1)* .18(.13-.25)Väderöarna 121 13 95-07 .28 (.20-.38)

Dab muscleFladen 3-6 5 5 89-94 -

Flounder mscVäderöarna 4-6 6 6 89-94 -

Blue mussel **Fladen 75 20 88-07 -7.2 (-8.8,-5.5)* .0530 (.042-.066)Väderöarna 72 19 88-07 -6.5 (-9.4,-3.5)* .052 (.040-.067)Kvädöfjärden 61 13 95-07 .063 (.059-.068)

Guillemot eggSt. Karlsö 198 20 88-07 -6.9 (-8.3,-5.5)* 2.3 (2.0-2.7)* significant trend, p < 0.05

** Pooled samples

95

sPCB, ug/g lipid w., herring muscle

Harufjarden (3-4)

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

80 85 90 95 00 05

n(tot)=382,n(yrs)=28m=.623 (.451,.860)slope=-8.9%(-10,-7.6)SD(lr)=64,2.1%,16 yrpower=1.0/.24/11%y(07)=.180 (.144,.225)r2=.87, p<.001 *tao=-.77, p<.001 *SD(sm)=55, p<.080,9.5%slope=-5.0%(-12,1.5)SD(lr)=20,9.5%,15 yrpower=.32/.32/9.5%r2=.28, NS

Angskarsklubb (3-5)

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

80 85 90 95 00 05

n(tot)=353,n(yrs)=28m=1.03 (.783,1.37)slope=-7.7%(-8.9,-6.6)SD(lr)=779,1.8%,15 yrpower=1.0/.32/9.5%y(07)=.354 (.292,.429)r2=.87, p<.001 *tao=-.79, p<.001 *SD(sm)=671, p<.083,8.2%slope=-9.6%(-14,-5.5)SD(lr)=25,5.8%,11 yrpower=.68/.68/5.8%r2=.78, p<.001 *

Landsort (3-5)

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

80 85 90 95 00 05

n(tot)=383,n(yrs)=29m=1.38 (1.13,1.70)slope=-5.4%(-6.7,-4.2)SD(lr)=83,1.8%,15 yrpower=1.0/.30/9.9%y(07)=.645 (.528,.787)r2=.76, p<.001 *tao=-.69, p<.001 *SD(sm)=73, p<.099,8.6%slope=-11%(-17,-5.1)SD(lr)=90,8.5%,14 yrpower=.38/.38/8.5%r2=.70, p<.003 *

Utlangan (3-4)

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

80 85 90 95 00 05

n(tot)=291,n(yrs)=28m=1.12 (.918,1.36)slope=-5.4%(-6.6,-4.2)SD(lr)=226,1.8%,15 yrpower=1.0/.33/9.3%y(07)=.538 (.444,.652)r2=.76, p<.001 *tao=-.70, p<.001 *SD(sm)=195, p<.086,8.0%slope=-6.2%(-14,1.3)SD(lr)=76,11%,16 yrpower=.25/.25/11%r2=.31, p<.091

pia - 09.04.15 14:50, PSSC

sPCB, ug/g lipid w., herring muscleFat adjusted geometric means (spring)

Angskarsklubb (2-5) spring

0

4

8

12

16

20

24

28

32

36

75 80 85 90 95 00 05

n(tot)=623,n(yrs)=34m=2.69 (2.14,3.37)slope=-5.1%(-6.2,-3.9)SD(lr)=36,1.8%,18 yrpower=1.0/.19/13%y(07)=1.13 ( .89,1.43)r2=.71, p<.001 *tao=-.65, p<.001 *SD(sm)=40, NS,15%slope=-8.3%(-18,1.9)SD(lr)=129,15%,20 yrpower=.16/.16/15%r2=.30, p<.096

Karlskrona (2-4) spring

0

4

8

12

16

20

24

28

32

36

75 80 85 90 95 00 05

n(tot)=614,n(yrs)=33m=3.34 (2.28,4.91)slope=-9.9%(-11,-9.0)SD(lr)=21,1.4%,15 yrpower=1.0/.32/9.4%y(07)=.629 (.529,.747)r2=.95, p<.001 *tao=-.86, p<.001 *SD(sm)=19, NS,8.5%slope=-10%(-17,-3.3)SD(lr)=433,9.8%,15 yrpower=.30/.30/9.8%r2=.59, p<.009 *

Fladen (2-3)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

80 85 90 95 00 05

n(tot)=469,n(yrs)=28m=.428 (.331,.555)slope=-7.6%(-8.7,-6.5)SD(lr)=28,1.6%,14 yrpower=1.0/.37/8.6%y(07)=.154 (.129,.184)r2=.88, p<.001 *tao=-.81, p<.001 *SD(sm)=31, NS,9.5%slope=-13%(-18,-7.7)SD(lr)=13,7.3%,13 yrpower=.49/.49/7.3%r2=.81, p<.001 *

pia - 09.04.16 13:37, PSSV

96

sPCB, ug/g lipid w., Guillemot eggs, early laid. St Karlso

0

100

200

300

400

500

600

68 70 72 74 76 78 80 82 84 86 88 90 92 94 96 98 00 02 04 06

n(tot)=380,n(yrs)=36m=68.0 (48.4,95.5)slope=-9.0%(-9.6,-8.4)SD(lr)=.19,.90%,12 yrpower=1.0/.54/6.9%y(06)=13.7 (12.1,15.5)r2=.97, p<.001 *tao=-.90, p<.001 *SD(sm)=.18, NS,7.7 %slope=-9.0%(-15,-3.3)SD(lr)=.22,8.1%,14 yrpower=.41/.41/8.1%r2=.63, p<.006 *

pia - 07.03.12 14:26, PSSU

CB-153, ug/g lipid w., herring muscle

Harufjarden (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

90 95 00 05

n(tot)=266,n(yrs)=19m=.050 (.041,.062)slope=-4.1%(-7.3,-.97)SD(lr)=12,4.7%,19 yrpower=.86/.18/14%y(07)=.034 (.025,.048)r2=.31, p<.013 *tao=-.36, p<.033 *SD(sm)=13, NS,15%

Angskarsklubb (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

90 95 00 05

n(tot)=287,n(yrs)=19m=.127 (.103,.158)slope=-5.9%(-8.6,-3.1)SD(lr)=15,3.9%,17 yrpower=.95/.23/12%y(07)=.075 (.056,.101)r2=.54, p<.001 *tao=-.49, p<.004 *SD(sm)=12, p<.039,8.9%

Landsort (3-5)

.0

.1

.2

.3

.4

.5

.6

.7

90 95 00 05

n(tot)=304,n(yrs)=21m=.106 (.084,.134)slope=-4.7%(-8.0,-1.3)SD(lr)=20,4.8%,21 yrpower=.84/.14/17%y(07)=.067 (.045,.098)r2=.31, p<.009 *tao=-.43, p<.007 *SD(sm)=15, p<.021,12%

Utlangan (3-4)

.0

.1

.2

.3

.4

.5

.6

.7

90 95 00 05

n(tot)=267,n(yrs)=20m=.094 (.078,.112)slope=-2.5%(-5.5,.46)SD(lr)=15,4.2%,18 yrpower=.92/.18/14%y(07)=.074 (.053,.102)r2=.15, p<.090tao=-.19, NSSD(sm)=10, p<.007,8.9%

pia - 09.04.15 14:26, 153C

97

CB-153, ug/g lipid w., herring muscle

Vaderoarna

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

n(tot)=231,n(yrs)=12m=.023 (.019,.028)slope=-2.8%(-8.3,2.7)SD(lr)=8.1,8.3%,17 yrpower=.39/.24/11%y(07)=.019 (.013,.028)r2=.12, NStao=-.18, NSSD(sm)=8.8, NS,12%


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

90 95 00 05

n(tot)=259,n(yrs)=19m=.215 (.172,.269)slope=-2.4%(-6.4,1.7)SD(lr)=30,5.8%,21 yrpower=.68/.13/17%y(07)=.174 (.114,.266)r2=.08, NStao=-.11, NSSD(sm)=36, NS,21%

Karlskrona, spring

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

90 95 00 05

n(tot)=254,n(yrs)=19m=.174 (.140,.216)slope=-6.0%(-8.4,-3.6)SD(lr)=16,3.6%,16 yrpower=.98/.26/11%y(07)=.100 (.077,.130)r2=.62, p<.001 *tao=-.60, p<.001 *SD(sm)=15, NS,9.7%

Fladen (2-3)

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

90 95 00 05

n(tot)=324,n(yrs)=20m=.044 (.036,.055)slope=-6.2%(-8.3,-4.1)SD(lr)=8.2,3.0%,15 yrpower=1.0/.32/9.4%y(07)=.025 (.019,.031)r2=.69, p<.001 *tao=-.66, p<.001 *SD(sm)=8.8, NS,10%

pia - 09.04.16 13:42, 153V

CB-153, ug/g lipid w., cod liver

SE Gotland (3-4)

.0

.2

.4

.6

.8

1.0

1.2

1.4

90 95 00 05

.0

.2

.4

.6

.8

1.0

1.2

1.4

n(tot)=152,n(yrs)=19m=.185 (.164,.210)slope=-1.8%(-4.0,.31)SD(lr)=14,3.1%,14 yrpower=1.0/.36/8.8%y(07)=.157 (.126,.197)r2=.16, p<.086tao=-.20, NSSD(sm)=16, NS,9.7%

Fladen (2-3)

.0

.2

.4

.6

.8

1.0

1.2

1.4

90 95 00 05

.0

.2

.4

.6

.8

1.0

1.2

1.4

n(tot)=146,n(yrs)=18m=.438 (.362,.530)slope=-.71%(-4.3,2.9)SD(lr)=48,5.4%,19 yrpower=.73/.16/15%y(07)=.412 (.284,.596)r2=.01, NStao=-.03, NSSD(sm)=41, NS,13%

pia - 09.04.15 14:30, 153G

98

CB-153, ug/g lipid w., perch muscle

Holmoarna


.00

.05

.10

.15

.20

.25

.30

.35

.40

.45

90 95 00 05

m=.100 (.065,.135)slope=-11%(-16,-5.6)SD(lr)=12,7.5%,17 yrpower=.46/.22/12%y(07)=.039 (.027,.056)r2=.66, p<.001 *tao=-.62, p<.003 *SD(sm)=307, p<.001,100%

Kvadofjarden


.00

.05

.10

.15

.20

.25

.30

.35

.40

.45

85 90 95 00 05

m=.052 (.039,.069)slope=-6.8%(-11,-2.8)SD(lr)=15,5.8%,21 yrpower=.68/.13/17%y(07)=.027 (.017,.041)r2=.43, p<.003 *tao=-.50, p<.003 *SD(sm)=3861, p<.001,100%

pia - 09.04.15 14:29, 153P

CB-153, ug/g lipid w. Eelpout muscle

Holmoarna

n(tot)=96,n(yrs)=11

.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

m=.145 (.099,.212)slope=-3.0%(-14,7.7)SD(lr)=30,19%,25 yrpower=.12/.10/23%y(07)=.122 (.059,.253)r2=.04, NStao=-.05, NS

Kvadofjarden


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

m=.177 (.128,.247)slope=-11%(-17,-5.1)SD(lr)=21,8.4%,18 yrpower=.38/.19/13%y(07)=.092 (.061,.139)r2=.61, p<.002 *tao=-.59, p<.005 *

Vaderoarna


.0

.1

.2

.3

.4

.5

.6

.7

.8

.9

94 96 98 00 02 04 06

m=.275 (.199,.379)slope=.55%(-8.5,9.6)SD(lr)=43,13%,24 yrpower=.18/.10/21%y(07)=.284 (.150,.539)r2=.00, NStao=.03, NS

pia - 09.04.02 14:25, 153Z

99

CB-153, ug/g lipid w., blue mussel

Fladen

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

.20

.22

90 95 00 05

n(tot)=75,n(yrs)=20m=.053 (.042,.066)slope=-7.2%(-8.8,-5.5)SD(lr)=6.8,2.3%,13 yrpower=1.0/.49/7.3%y(07)=.027 (.022,.032)r2=.82, p<.001 *tao=-.73, p<.001 *SD(sm)=6.9, NS,7.4%

Vaderoarna

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

.20

.22

90 95 00 05

n(tot)=72,n(yrs)=19m=.052 (.040,.067)slope=-6.5%(-9.4,-3.5)SD(lr)=12,4.5%,18 yrpower=.89/.19/13%y(07)=.029 (.021,.039)r2=.56, p<.001 *tao=-.40, p<.016 *SD(sm)=7.2, p<.002,7.8%

Kvadofjarden

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

.20

.22

94 96 98 00 02 04 06

n(tot)=61,n(yrs)=13m=.063 (.059,.068)slope=-.02%(-2.0,2.0)SD(lr)=10,.60%,16 yrpower=1.0/.28/10%y(07)=.063 (.054,.073)r2=.00, NStao=-.12, NS

pia - 09.04.29 17:04, 153M

CB-153, ug/g lipid w., guillemot egg

St Karlso


0

2

4

6

8

10

12

14

16

18

90 95 00 05

m=4.44 (3.62,5.46)slope=-6.9%(-8.3,-5.5)SD(lr)=11.4,2.0%,12 yrpower=1.0/.63/6.1%y(07)=2.31 (1.98,2.70)r2=.86, p<.001 *tao=-.81, p<.001 *SD(sm)=15.0, NS,8.1%

pia - 08.03.25 16:21, 153u

100

19 DDT's,Dichlorodiphenylethanes

Updated 09.05.31

The concentration of DDT’s in fish muscle and blue mussel soft body is determined using agas chromatograph (GC) equipped with an electron capture detector.

Before 1988 DDT’s (DDT, DDE, DDD) were analysed on a packed column GC. During1988, analyses on capillary column were introduced. The two methods give slightlydifferent results for the various DDT-compounds. In table 19.1 the mean ratio: ‘capillarycolumn results’ / ‘packed column results’ from various sites and matrices are presented.When the concentrations are close to the detection limit (D.L.) for packed column GC theresults seem to be underestimated. This is particularly true for the estimated sum of DDT’s(sDDT) since DDT and DDD may fall below D.L. and hence only DDE will constitute thesum. To avoid this bias at low levels, only samples with DDE concentrations above 0.2g/g have been selected to calculate the ratios given below. Only analyses where DDE,DDD and DDT were all present in levels above D.L. are included in the sDDT ratio. Whenit has been possible to estimate these ratios, they are in general close to 1. There are a fewexceptions; at Landsort both the DDE and DDT ratios are lower than 1, indicatingoverestimated concentrations from the packed column, possible due to interference withother compounds in the DDE and DDT peaks in the packed column chromatogramme. AtFladen the DDE ratio is significantly above 1 indicating underestimated DDE concentrationfrom the packed column GC.

In the time series presented below DDE is shown for herring, cod perch, eelpout and bluemussel and sDDT for flounder, dab and guillemot where the ratio of 1 has been used.

Table 19.1. Ratios of DDE, DDT, DDD and sDDT analysed on a capillary column versus the same samplesanalysed on a packed column gas chromatography (GC) and the corresponding 95% confidence interval.

n DDE 95% C.I.. n DDT 95% C.I.. n DDD 95% C..I. n sDDT 95% C.I.

Herring muscleHarufjärden 6 1.1 .99-1.2 6 .96 .89-1.0 4 1.5 1.1-2.0 4 1.1 .98-1.2Ängskärsklubb 16 1.1 1.0-1.2 - - - 15 .63 .55-.70 - - -

Spring 24 1.0 1.0-1.1 1 .62 - 21 .77 .68-.85 1 .75 -Landsort 28 .79 .76-.82 28 .75 .67-.81 28 .87 .77-.96 27 .79 .77-.82Utlängan 20 1.1 1.0-1.1 20 1.0 .98-1.1 20 1.1 1.1-1.2 20 1.1 1.0-1.1

Spring 20 1.1 1.1-1.1 10 .81 .74-.88 10 1.1 1.0-1.1 10 1.0 .98-1.1Fladen 6 1.4 1.3-1.4 5 .90 .77-1.0 6 1.1 .94-1.3 4 1.2 1.1-1.3Cod liverSE Gotland 6 1.0 .95-1.1 - - - - - -Fladen 8 1.1 1.0-1.1 - - - - - -Dab muscleFladen 9 1.0 .92-1.1Flounder muscleVäderöarna 1.0 .86-1.2Guillemot eggSt. Karlsö 30 1.2 1.1-1.2 - - - - - -

The detection limit (capillary column, GC) is estimated to approximately 7 ng/g fat weightfor DDE, 4 ng/g for DDD and 3 ng/g for DDT.

101



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the DDT discharges are to be reduced by 50% between 1985 and1995, using 1985 as a base year.

The Helsinki Convention (HELCOM) revised 1992 especially names the DDTs for whichspecial bans and restrictions on transport, trade, handling, use and disposal are imposed.The Minister Declaration from 1988, within HELCOM, calls for a reduction of stableorganic substances by 50% by 1995 with 1987 as a base year.

In Sweden, DDT was partially banned as a pesticide in 1970, and completely banned in1975 due to its persistence and environmental impact.


DDE concentrations in herring muscle from all investigated sites and in cod , perch andblue mussels from the Kattegatt and Skagerack decreased significantly during the timeperiod 1980-2007. The rate varies between 4 and 11% a year. The time series of guillemoteggs (1969-2007) show a significant trend of -10% a year for sDDT.

The discharge of fresh DDT during 1983-84 (Bignert et al, 1990) is clearly noticeable in thetime series from Landsort and Utlängan in the Baltic proper and Fladen at the Swedish westcoast.

The number of years required to detect an annual change of 5% for DDE in herring variedbetween 15 to 21 years. The variation of DDE is somewhat less between years in generalcompared to DDT and DDD. When comparing the power of the time series of DDT's withother contaminants it should be noted that the DDT incident 1983-84 deteriorate the powerof the time series calculated from the log-linear regression lines.

The ratio of DDT/sDDT is decreasing significantly at all herring sites except forVäderöarna where there is not enough data points to detect a possible change.

19.1.3 Conclusion

The concentration of DDE has decreased at a rate of approximately 5-11% per year (inherring), in the Baltic as well as in the Kattegatt, since the end of the seventies. The DDThas generally decreased faster than the sum of DDT’s.

102


DDE

< 0.15

0.15 - 0.3

> 0.3

ug/g lw

TISS - 09.05.05 13:04, DDE

Figure 19.1. Spatial variation in concentration (l.w.) of DDE in herring muscle.

The highest concentraions of DDE in herring (lipid weight) is found at Hanöbukten (figure19.1, yet only one year is presented for the new localities) in the Baltic Proper, significantlyhigher than from Harufjärden (Bothnian Bay) and at the localities at the Swedish west coast.

The DDE concentrations in cod from the Baltic Proper (southeast of Gotland) are abouttwice as high, compared to cod from Fladen at the Swedish west coast.

103

Table 19.2. Estimated geometric mean concentrations of DDE (g/g lipid weight) in various matrices andsites for the last sampled year. For dab, flounder and guillemot sDDT is estimated (g/g lipid weight).

Matrix age n tot n yrs year trend last yrHerring msc.Harufj. autumn 3-4 432 28 78-07 -9.6 (-12,-7.5)* .026 (.018-.036)Ängskärskl. aut. 3-5 456 28 78-07 -8.3 (-9.6,-7.0)* .066 (.053-.081)

” spring 2-5 623 34 72-07 -7.1 (-8.4,-5.8)* .29 (.23-.38)Landsort 3-5 436 29 78-07 -5.0 (-6.5,-3.5)* .19 (.15-.25)Utlängan, aut. 3-4 349 28 80-07 -4.5 (-6.0,-3.0)* .18 (.14-.23)

” spring 2-3 577 33 72-07 -11 (-12, -10)* .17 (.14-.21)Fladen 2-3 499 28 80-07 -8.3 (-9.9-6.6)* .025 (.019-.032)Väderöarna 230 12 95-07 -4.9 (-11-.97)* .018 (.012-.028)

Cod liverSE Gotland 3-4 285 27 80-07 -5.3 (-6.7,-3.9)* .33 (.27-.41)Fladen 2-3 322 27 80-07 -5.5 (-7.1,-3.9)* .190 (.15-.24)

Perch muscleHolmöarna 279 22 80-07 -11 (-13,-9.2)* .024 (.028-.033)Kvädöfjärden 333 25 80-07 -11 (-14,-8.5)* .021 (.013-.033)

Eelpout muscleHolmöarna 95 11 95-07 .10 (.057-.18)Kvädöfjärden 120 13 95-07 -13 (-21,-5.2)* .076 (.044-.13)Väderöarna 119 13 95-07 .0750 (.045-.12)

Dab muscleFladen 3-5 184 14 81-94 .12 (.062-.23)

Flounder mscVäderöarna 4-6 163 15 80-94 .11 (.060-.20)

Blue musselFladen 73 22 82-07 -7.1 (-9.6,-4.6)* .023 (.016-.033)Väderöarna 75 22 84-07 -8.1 (-10,-5.9)* .014 (.011-.020)Kvädöfjärden 61 13 95-07 .070 (.059-.083)

Guillemot eggSt. Karlsö 380 36 69-07 -9.8 (-11,-8.8)* 10 (8.1-12)* significant trend, p < 0.05

Table 19.3. The estimated proportion of DDT, DDE, DDD, DDT (%) in various matrices and sites.Matrix age n yrs year DDT DDE DDDHerring msc.Harufj. autumn 3-4 78-95 33 60 7Ängskärskl. aut. 3-5 78-95 17 64 18Landsort 3-5 78-95 17 51 32Utlängan, aut. 2-4 80-95 19 49 32Fladen 2-3 80-95 22 55 23

Cod liverSE Gotland 3-4 80-95 17 56 27Fladen 2-4 80-95 10 76 14

Perch muscleHolmöarna 80-95 5 82 13Kvädöfjärden 3-5 80-95 6 85 9

Blue musselFladen 81-95 17 63 20Väderöarna 80-95 18 65 17

104

DDE, ug/g lipid w., herring muscle

Harufjarden (3-4)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

80 85 90 95 00 05

n(tot)=432,n(yrs)=28m=.098 (.068,.141)slope=-9.6%(-12,-7.5)SD(lr)=19,3.1%,21 yrpower=1.0/.13/17%y(07)=.026 (.018,.036)r2=.78, p<.001 *tao=-.65, p<.001 *SD(sm)=17, p<.068,14%slope=-4.0%(-14,5.8)SD(lr)=12,14%,19 yrpower=.17/.17/14%r2=.10, NS

Angskarsklubb (3-5)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

80 85 90 95 00 05

n(tot)=456,n(yrs)=28m=.209 (.155,.282)slope=-8.3%(-9.6,-7.0)SD(lr)=18,2.0%,16 yrpower=1.0/.27/11%y(07)=.066 (.053,.081)r2=.87, p<.001 *tao=-.78, p<.001 *SD(sm)=22, NS,13%slope=-11%(-18,-3.7)SD(lr)=12,10%,16 yrpower=.28/.28/10%r2=.60, p<.008 *

Landsort (3-5)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

80 85 90 95 00 05

n(tot)=436,n(yrs)=29m=.391 (.318,.481)slope=-5.0%(-6.5,-3.5)SD(lr)=35,2.2%,17 yrpower=1.0/.21/12%y(07)=.193 (.151,.247)r2=.64, p<.001 *tao=-.60, p<.001 *SD(sm)=32, NS,11%slope=-8.0%(-14,-2.4)SD(lr)=14,8.1%,14 yrpower=.41/.41/8.1%r2=.57, p<.011 *

Utlangan (3-4)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

80 85 90 95 00 05

n(tot)=349,n(yrs)=28m=.331 (.275,.399)slope=-4.5%(-6.0,-3.0)SD(lr)=28,2.1%,17 yrpower=1.0/.23/11%y(07)=.180 (.143,.228)r2=.60, p<.001 *tao=-.54, p<.001 *SD(sm)=24, p<.069,9.6%slope=-9.3%(-17,-1.4)SD(lr)=20,11%,17 yrpower=.24/.24/11%r2=.48, p<.025 *

pia - 09.04.15 15:12, DDEC

DDE, ug/g lipid w., herring muscleFat adjusted spring herring samples

Angskarsklubb (2-5) spring

0

2

4

6

8

10

12

14

16

75 80 85 90 95 00 05

n(tot)=623,n(yrs)=34m=.649 (.501,.842)slope=-5.9%(-7.2,-4.7)SD(lr)=90,2.0%,19 yrpower=1.0/.16/15%y(07)=.234 (.181,.303)r2=.74, p<.001 *tao=-.69, p<.001 *SD(sm)=109, NS,18%slope=-8.3%(-20,2.9)SD(lr)=38,17%,21 yrpower=.14/.14/17%r2=.27, NS

Karlskrona(2-3) spring

0

2

4

6

8

10

12

14

16

75 80 85 90 95 00 05

n(tot)=577,n(yrs)=33m=1.09 (.714,1.67)slope=-11%(-12,-10)SD(lr)=307,1.5%,15 yrpower=1.0/.29/9.9%y(07)=.172 (.144,.207)r2=.95, p<.001 *tao=-.88, p<.001 *SD(sm)=310, NS,10%slope=-11%(-18,-2.9)SD(lr)=24,11%,16 yrpower=.25/.25/11%r2=.56, p<.012 *

Fladen (2-3)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

80 85 90 95 00 05

n(tot)=499,n(yrs)=28m=.075 (.056,.101)slope=-8.3%(-9.9,-6.6)SD(lr)=13,2.3%,18 yrpower=1.0/.20/13%y(07)=.025 (.019,.032)r2=.81, p<.001 *tao=-.77, p<.001 *SD(sm)=14, NS,14%slope=-13%(-23,-3.3)SD(lr)=12,15%,19 yrpower=.17/.17/15%r2=.54, p<.015 *

Vaderoarna (2-3)

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

94 96 98 00 02 04 06

n(tot)=230,n(yrs)=12m=.025 (.020,.031)slope=-4.9%(-11,.97)SD(lr)=8.8,8.8%,17 yrpower=.36/.22/12%y(07)=.018 (.012,.028)r2=.26, p<.091tao=-.33, NSSD(sm)=9.9, NS,14%slope=-7.1%(-17,3.3)SD(lr)=9.7,17%,18 yrpower=.14/.18/14%r2=.27, NS

pia - 09.04.29 17:09, DDEV

105

DDE, ug/g lipid w., cod liver and perch muscle.Geometric means, fat adjusted

PerchCod (3-4), SE Gotland

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

80 85 90 95 00 05

n(tot)=285,n(yrs)=27m=.668 (.544,.820)slope=-5.3%(-6.7,-3.9)SD(lr)=70,2.1%,16 yrpower=1.0/.27/10%y(07)=.331 (.267,.411)r2=.71, p<.001 *tao=-.67, p<.001 *SD(sm)=84, NS,13%slope=-4.9%(-13,3.4)SD(lr)=39,12%,17 yrpower=.21/.21/12%r2=.19, NS

Cod (2-3), Fladen

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

80 85 90 95 00 05

n(tot)=322,n(yrs)=27m=.395 (.316,.494)slope=-5.5%(-7.1,-3.9)SD(lr)=36,2.4%,17 yrpower=1.0/.21/12%y(07)=.189 (.147,.242)r2=.67, p<.001 *tao=-.63, p<.001 *SD(sm)=22, p<.001,7.6%slope=-11%(-18,-4.9)SD(lr)=20,9.1%,15 yrpower=.34/.34/9.1%r2=.68, p<.003 *

Holmoarna

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

80 85 90 95 00 05

n(tot)=279,n(yrs)=22m=.103 (.063,.166)slope=-11%(-13,-9.2)SD(lr)=17,3.8%,19 yrpower=.97/.17/14%y(07)=.024 (.018,.033)r2=.88, p<.001 *tao=-.82, p<.001 *SD(sm)=11, p<.007,9.5%slope=-9.7%(-18,-1.7)SD(lr)=9.8,12%,17 yrpower=.23/.23/12%r2=.50, p<.023 *

Kvadofjarden (3-4)

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

80 85 90 95 00 05

n(tot)=233,n(yrs)=25m=.096 (.060,.152)slope=-11%(-14,-8.5)SD(lr)=25,4.8%,25 yrpower=.84/.10/22%y(07)=.021 (.013,.033)r2=.74, p<.001 *tao=-.66, p<.001 *SD(sm)=19, p<.032,17%slope=-9.6%(-23,4.0)SD(lr)=16,24%,23 yrpower=.09/.11/20%r2=.29, NS

pia - 09.05.28 12:39, DDEGP

DDE, ug/g lipid w., Eelpout

Holmoarna

n(tot)=95,n(yrs)=11

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

94 96 98 00 02 04 06

m=.112 (.084,.150)slope=-2.0%(-10,6.2)SD(lr)=21,14%,21 yrpower=.17/.13/17%y(07)=.100 (.057,.176)r2=.03, NStao=-.13, NS

Kvadofjarden


.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

94 96 98 00 02 04 06

m=.166 (.110,.251)slope=-13%(-21,-5.2)SD(lr)=27,11%,22 yrpower=.23/.12/18%y(07)=.076 (.044,.132)r2=.55, p<.004 *tao=-.56, p<.007 *

Vaderoarna


.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

94 96 98 00 02 04 06

m=.083 (.065,.108)slope=-1.8%(-8.9,5.3)SD(lr)=18,10%,21 yrpower=.27/.14/17%y(07)=.075 (.045,.124)r2=.03, NStao=-.10, NS

pia - 09.04.15 15:27, DDEZ

106

DDE, ug/g lipid w., blue mussel

Fladen

.00

.05

.10

.15

.20

.25

.30

.35

.40

85 90 95 00 05

.00

.05

.10

.15

.20

.25

.30

.35

.40

n(tot)=73,n(yrs)=22m=.054 (.040,.073)slope=-7.1%(-9.6,-4.6)SD(lr)=14,4.2%,20 yrpower=.92/.15/16%y(07)=.023 (.016,.033)r2=.64, p<.001 *tao=-.65, p<.001 *SD(sm)=18, NS,20%slope=-6.6%(-16,2.3)SD(lr)=9.3,15%,17 yrpower=.16/.21/12%r2=.31, NS

Vaderoarna

.00

.05

.10

.15

.20

.25

.30

.35

.40

85 90 95 00 05

.00

.05

.10

.15

.20

.25

.30

.35

.40

n(tot)=75,n(yrs)=22m=.037 (.027,.050)slope=-8.1%(-10,-5.9)SD(lr)=11,3.6%,18 yrpower=.98/.19/13%y(07)=.014 (.011,.020)r2=.74, p<.001 *tao=-.65, p<.001 *SD(sm)=10, NS,13%slope=-3.1%(-9.1,2.9)SD(lr)=5.6,9.7%,14 yrpower=.31/.42/8.0%r2=.17, NS

Kvadofjarden

.00

.05

.10

.15

.20

.25

.30

.35

.40

94 96 98 00 02 04 06

.00

.05

.10

.15

.20

.25

.30

.35

.40

n(tot)=61,n(yrs)=13m=.071 (.066,.078)slope=-.36%(-2.6,1.9)SD(lr)=12,.80%,17 yrpower=1.0/.23/12%y(07)=.070 (.059,.083)r2=.00, NStao=-.22, p<.016 *

pia - 09.04.29 17:07, DDEM

sDDT, ug/g lipid w., guillemot egg, early laid

0

100

200

300

400

500

600

70 75 80 85 90 95 00 05

n(tot)=380,n(yrs)=36m=62.4 (42.3,91.9)slope=-9.8%(-11,-8.8)SD(lr)=7.74,1.5%,17 yrpower=1.0/.22/12%y(07)=10.0 ( 8.1,12.4)r2=.92, p<.001 *tao=-.90, p<.001 *SD(sm)=3.93, p<.001,5.9%slope=-4.2%(-9.7,1.3)SD(lr)=7.08,8.8%,13 yrpower=.36/.48/7.3%r2=.32, NS

pia - 08.03.10 14:36, DSSU

107

20 HCH’s,Hexachlorocyclohexanes

Updated 09.05.31

Technical HCH contains various isomers: 60-75% -HCH, 15% -HCH (lindane), 7-10%-HCH, -HCH 7%, -HCH 1-2% and came into general use in 1950 (Gaul, 1992). The -isomer is the most toxic isomer of the HCH’s, 500 to 1000 times as active as the -isomer(White-Stevens, 1971). The use of technical HCH stopped in the countries around theBaltic between 1970-1980. Since 1980, use of lindane in Europe has been allowed only asan insecticide. It was still used to a great extent in France and Italy 1990 (Yi-Fan et al.1996)

The isomers: -HCH, ß-HCH and -HCH i.e. Lindane have been analysed in muscle tissuefor various fish species (liver tissue for cod), blue mussel soft body and guillemot eggssince 1988, see table below. Samples from 1987 at Harufjärden and Landsort have beenretrospectively analysed. The concentrations of ß-HCH are in many cases close to thedetection limit, which implies analytical problems.

The detection limit is estimated to approximately 2 ng/g fat weight for -HCH, 3 ng/g for-HCH and 3 ng/g for -HCH.



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the discharges of HCHs are to be reduced by 50% between 1985 and1995, using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of stableorganic substances by 50% by 1995 with 1987 as a base year.

In Sweden, the use of lindane was severely restricted 1970, subsequently prohibited for usein agriculture 1978 because of its suspected carcinogenic properties and persistence.Remaining use was banned 1988/89.


The variance for concentrations of -HCH in herring muscle is generally low. Decreasingtrends with an annual decrease of about 13-20% are found for herring from all sites. Theconcentrations in cod liver are also decreasing significantly both in the time series fromsouth east of Gotland and Fladen (in Kattegatt at the Swedish west coast).Concentrations of-HCH are also decreasing in perch from Kvädöfjärden and Holmöarna, in eelpout from the

108

same sampling sites as perch as well as in eelpout from Väderöarna and in guillemot eggsfrom St Karlsö.

The number of years required to detect an annual change of 5% is about 10-13 years for codand varies between 7 to 14 years for the herring time series.

Concentrations of β-HCH are generally decreasing, and are now approaching the detectionlimit. This makes the substance less fitted for use in this kind of study. The concentrationsof ß-HCH in some matrices are however still detectable and show significant decreasingtrends, for example in herring from Ängskärsklubb, Landsort and Utlängan, in cod from SEGotland and in guillemot eggs.

The concentration of lindane (-HCH) has decreased significantly in all analysed matrices atall sampling sites except for guillemot eggs (St Karlsö) and herring from Väderöarna. Thedecrease is in the magnitude of 10 to 18% for herring, perch, and blue mussel and 15 to20% for cod and eelpout.

The ratio -HCH/lindane in herring, show significant decreasing trends from Harufjärden,Landsort and Utlängan.

20.1.3 Conclusion

In general, the concentration of HCH's seems to have decreased at a rate of about 10% ormore per year, in various species from the Baltic as well as at the Swedish west coast, sincethe end of the eighties. From ten time series on herring, cod and guillemot eggs for theperiod 1987-95, a median decrease of 65 % (38-88%) could be estimated. -HCH is ingeneral decreasing faster than lindane.

Measures taken to fulfil the aim of the North Sea Conference and the HELCOMConvention of a 50% reduction of the discharges of HCHs, 1995 with 1985 and 1987respectively as base years, thus seems to have had a measurable effect in biota.

109


b-HCH

< 5

5 - 10

> 10

ng/g lw

TISS - 09.05.05 13:19, bHCH

Figure 20.1. Spatial variation in concentration (l.w.) of b-HCH in herring muscle.

Somewhat higher concentrations of HCH's (lipid weight) are found in the herring samplesfrom the Baltic Proper compared to the Bothnian Bay and the Kattegatt even after the rapiddecrease mentioned above, see tables 20.1 and 20.2.

Figure 20.1 also show higher concentrations of b-HCH in herring from the Baltic Properthan in herring from the Bothnian Sea and the Swedish West Coast. Bare in mind thatresults from the new sampling sites are based on analysis from one year only.

The ratio lindane/-HCH is higher in the Kattegatt compared to the Baltic in both herringand cod. This could reflect that in the former east-bloc countries mainly technical HCHwere used whereas the use of lindane (-HCH) was more common in western countries.


Unlike the PCB’s, the DDT’s and HCB, the HCH’s show no significant seasonal differencein concentrations between herring caught in the spring and in the autumn.

110

Table 20.1. Geometric mean concentrations of a-HCH (ug/g lipid weight) in various matrices and sites duringthe studied time period and the estimated mean concentration for the last year. The age interval for fish, andthe length interval for blue mussels are also presented together with the total number of analyses and thenumber of years of the various time-series.

Matrix age n n yrs year trend (95% ci) Last year (95%ci)

Herring msc.Harufj. autumn 3-4 168 11 87, 90-99# -16 (-19,-13)* .**Ängskärskl. aut. 3-5 243 16 89-04# -20 (-23,-17)* **

” spring 2-4 197 16 89-07 -18(-19,-17)* .003 (.003-.003)Landsort 3-5 296 21 87-07 -18 (-19,-16)* .004 (.003,.004)Utlängan, aut. 3-4 249 20 88-07 -18 (-19,-17)* .003 (.003-.003)

” spring 2-3 212 18 87-07 -18 (-19,-17)* .003 (.003-.004)Fladen 2-3 243 14 88-01# -16 (-17,-15)* **Väderöarna 107 7 95-99, 03# -13 (-17, -9.6)* **

Cod liverSE Gotland 165 19 89-07 -19 (-20,-18)* .003(.003-.004)Fladen 130 18 89-06# -16 (-18,-14) .002 (.001-.002)

Perch muscleHolmöarna 43 5 89,95-98# -16 (-20,-12)* **Kvädöfjärden 116 14 84, 89-01,06# -19 (-22,-16)* .001 (.001-.002)

EelpoutHolmöarna 34 6 95,97,99-02# -16 (-26, -6.1)* **Kvädöfjärden 48 8 95-02# -16 (-21, -9.8)* **Väderöarna 30 4 95,96,98,05# .004 (.001-.013)

Blue musselKvädöfjärden 60 12 95-07 -15 (-18,-13)* .004 (.004-.005)Fladen 48 14 88-01# -15 (-18,-12)* **Väderöarna 48 14 88-04# -13 (-17,-9.6)* **

Guillemot eggSt. Karlsö 158 17 88-07 -14 (-17,-12)* .003 (.002-.004)

# All values at or below detection limit during recent years


** No estimated value because of concentrations at or below detection limit

111

Table 20.2. Geometric mean concentrations of γ-HCH (Lindane) (ug/g lipid weight) in various matrices andsites during the studied time period and the estimated mean concentration for the last year. The age interval forfish is also presented together with the total number of analyses and the number of years of the various time-series.

Matrix age n n yrs year trend (95% ci) Last year (95% ci)Herring msc.Harufj. autumn 3-4 183 13 87, 90-01# -10 (-13,-7.7)* **Ängskärskl. aut. 3-5 229 15 89-03# -16 (-19, -12)* **

” spring 2-5 214 17 89-05# -14 (-16, -12)* **Landsort 3-5 285 20 87-06# -13 (-14, -12)* .005 (.005-006)Utlängan, aut. 2-4 278 19 88-06# -14 (-15, -13)* .005 (.004-.006)

” spring 2-3 204 18 87-06# -16 (-17, -14)* .005 (.004-.005)Fladen 2-3 252 14 88-01# -9.9 (-14,-5.6)* **Väderöarna 120 7 95-01# **

Cod liverSE Gotland 3-4 140 18 89-06# -15 (-16, -13)* .005 (.004-.006)Fladen 2-3 106 16 89-06# -18 (-21, -14)* .002 (.002-.003)

Perch muscleHolmöarna 41 5 89,95-98# -14 (-26, -3.1)* **Kvädöfjärden 72 9 89, 94-01# -11 (-20, -2.9)* **

EelpoutHolmöarna 30 5 95,97,99, 01-02# -17 (-32, -3.2)* **Kvädöfjärden 60 8 95-02# -18 (-21, -15)* **Väderöarna 69 8 95-02,05# -20 (-28, -12)* **

Blue musselKvädöfjärden 57 12 95-06# -16 (-20, -12)* .004 (.003-.006)Fladen 53 16 81, 83, 88-01# -9.5 (-12, -6.5)* **Väderöarna 50 15 83, 88-04# -12 (-16, -8.5)* **

Guillemot eggSt. Karlsö 96 13 88-91,93-97,00-

01,07.006 (.003-.011)

# all values below detection limit during recent years


** no estimated value because of concentrations at or below detection limit

Table 20.3. The estimated proportion of -, -, - HCH (%) in various matrices and sites.Matrix age n yrs year Herring msc.Harufj. autumn 3-4 7 87, 90-95 57 16 27Ängskärskl. aut. 3-5 7 89-95 49 22 28

” spring 2-5 7 89-95 48 26 26Landsort 3-5 9 87-95 47 25 28Utlängan, aut. 2-4 8 88-95 43 27 30

” spring 2-3 7 87-95 43 24 33Fladen 2-3 7 87-95 37 10 53

Cod liverSE Gotland 3-4 7 87-95 45 28 27Fladen 2-4 7 87-95 37 11 52

Blue musselFladen 10 81-95 32 11 57Väderöarna 8 83-95 31 9 60

112

a-HCH, ug/g lipid w., herring muscleHarufjarden (3-4)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=168,n(yrs)=11m=.020 (.013,.030)slope=-16%(-19,-13)SD(lr)=4.0,4.1%,10 yrpower=.93/.84/4.8%y(99)=.009 (.007,.011)r2=.94, p<.001 *tao=-.93, p<.001 *SD(sm)=4.3, NS,5.1%

Angskarsklubb (3-5)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05


Landsort (3-5)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=296,n(yrs)=21m=.021 (.013,.035)slope=-18%(-19,-16)SD(lr)=4.9,1.8%,11 yrpower=1.0/.70/5.8%y(07)=.004 (.003,.004)r2=.97, p<.001 *tao=-.94, p<.001 *SD(sm)=5.1, NS,6.0%

Utlangan (3-4)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05


pia - 09.04.15 17:51, HCHAC

a-HCH, ug/g lipid w., herring

Angskarsklubb, spring (2-4)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05


Karlskrona, spring (2-3)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=212,n(yrs)=18m=.018 (.010,.030)slope=-18%(-19,-17)SD(lr)=3.6,1.8%,10 yrpower=1.0/.88/4.5%y(07)=.003 (.003,.004)r2=.98, p<.001 *tao=-.97, p<.001 *SD(sm)=2.7, p<.041,3.3%

Fladen (2-3)

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=243,n(yrs)=14m=.010 (.007,.015)slope=-16%(-17,-15)SD(lr)=2.0,1.6%,7 yrpower=1.0/1.0/2.7%y(01)=.004 (.003,.004)r2=.98, p<.001 *tao=-.98, p<.001 *SD(sm)=1.9, NS,2.7%

Vaderoarna

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=107,n(yrs)=7m=.006 (.004,.008)slope=-13%(-17,-9.5)SD(lr)=2.1,6.0%,8 yrpower=.68/.99/3.2%y(03)=.003 (.003,.004)r2=.94, p<.001 *tao=-.90, p<.004 *SD(sm)=2.8, NS,4.3%

pia - 09.04.16 13:47, hchav

113

a-HCH, ug/g lipid w., cod liver and perch muscle

Cod, SE Gotland

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05


Cod (2-3), Fladen

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05


Perch, Holmoarna

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=43,n(yrs)=5m=.009 (.005,.018)slope=-16%(-20,-12)SD(lr)=1.8,12%,8 yrpower=.24/1.0/3.1%y(98)=.006 (.005,.007)r2=.98, p<.003 *tao=-.80, p<.050

Perch, Kvadofjarden

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

85 90 95 00 05

n(tot)=116,n(yrs)=14m=.011 (.006,.021)slope=-19%(-22,-16)SD(lr)=6.3,5.8%,16 yrpower=.67/.27/10%y(06)=.001 (.001,.002)r2=.94, p<.001 *tao=-.85, p<.001 *SD(sm)=5.2, NS,8.6%

pia - 09.04.15 17:56, HCHAGP

a-HCH, ug/g lipid w., blue mussel

Fladen

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.10

90 95 00 05


Vaderoarna

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.10

90 95 00 05

n(tot)=48,n(yrs)=14m=.010 (.006,.015)slope=-14%(-18,-9.3)SD(lr)=7.8,7.5%,18 yrpower=.46/.18/13%y(04)=.003 (.002,.005)r2=.79, p<.001 *tao=-.80, p<.001 *SD(sm)=6.7, NS,11%

Kvadofjarden

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.10

94 96 98 00 02 04 06

n(tot)=61,n(yrs)=13m=.012 (.010,.014)slope=-15%(-18,-13)SD(lr)=7.4,.70%,17 yrpower=1.0/.21/12%y(07)=.004 (.004,.005)r2=.74, p<.001 *tao=-.78, p<.001 *

pia - 09.04.29 17:11, HCHAM

114

b-HCH, ug/g lipid w., guillemot egg, early laid

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

88 90 92 94 96 98 00 02 04 06

n(tot)=198,n(yrs)=20m=.411 (.313,.539)slope=-9.4%(-11,-7.9)SD(lr)=20.2,2.1%,12 yrpower=1.0/.58/6.5%y(07)=.169 (.143,.198)r2=.91, p<.001 *tao=-.79, p<.001 *SD(sm)=16.1, p<.050,5.2%

pia - 08.03.12 10:36, hchbu

Lindane, ug/g lipid w., herring muscleHarufjarden (3-4)

.00

.02

.04

.06

.08

.10

.12

.14

90 95 00 05

n(tot)=183,n(yrs)=13m=.010 (.008,.013)slope=-10%(-13,-7.7)SD(lr)=3.5,3.7%,11 yrpower=.97/.68/5.8%y(01)=.005 (.004,.006)r2=.88, p<.001 *tao=-.87, p<.001 *SD(sm)=2.4, p<.040,4.0%

Angskarsklubb (3-5)

.00

.02

.04

.06

.08

.10

.12

.14

90 95 00 05

n(tot)=229,n(yrs)=15m=.013 (.008,.019)slope=-16%(-19,-12)SD(lr)=6.4,5.2%,16 yrpower=.78/.28/10%y(03)=.004 (.003,.006)r2=.87, p<.001 *tao=-.90, p<.001 *SD(sm)=7.7, NS,13%

Landsort (3-5)

.00

.02

.04

.06

.08

.10

.12

.14

90 95 00 05


Utlangan (2-5)

.00

.02

.04

.06

.08

.10

.12

.14

90 95 00 05


pia - 09.04.15 18:09, HCHGC

115

Lindane, ug/g lipid w., herring

Angskarsklubb spring (2-5)

.00

.02

.04

.06

.08

.10

.12

90 95 00 05


Karlskrona spring (2-3)

.00

.02

.04

.06

.08

.10

.12

90 95 00 05


Fladen (2-3)

.00

.02

.04

.06

.08

.10

.12

90 95 00 05

n(tot)=252,n(yrs)=14m=.019 (.014,.025)slope=-9.9%(-14,-5.6)SD(lr)=7.4,6.1%,16 yrpower=.63/.25/11%y(01)=.010 (.007,.014)r2=.68, p<.001 *tao=-.74, p<.001 *SD(sm)=4.8, p<.013,6.9%

Vaderoarna

.00

.02

.04

.06

.08

.10

.12

90 95 00 05

n(tot)=120,n(yrs)=7m=.011 (.006,.019)slope=-18%(-42,6.1)SD(lr)=11,39%,22 yrpower=.07/.12/19%y(01)=.006 (.003,.015)r2=.43, NStao=-.43, NSSD(sm)=9.8, NS,17%

pia - 09.04.16 13:48, hchgv

Lindane, ug/g lipid w., cod liver and perch muscle


.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

90 95 00 05


Cod (2-3), Fladen

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

90 95 00 05

n(tot)=106,n(yrs)=16m=.010 (.006,.017)slope=-18%(-21,-14)SD(lr)=7.8,6.0%,18 yrpower=.65/.19/13%y(06)=.002 (.002,.003)r2=.88, p<.001 *tao=-.82, p<.001 *SD(sm)=6.0, p<.061,10%

Perch, Holmoarna

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

90 95 00 05

n(tot)=41,n(yrs)=5m=.007 (.004,.015)slope=-14%(-26,-2.9)SD(lr)=5.2,41%,15 yrpower=.07/.32/9.4%y(98)=.005 (.003,.008)r2=.84, p<.031 *tao=-.40, NS

Perch, Kvadofjarden

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

90 95 00 05

n(tot)=66,n(yrs)=9m=.009 (.006,.014)slope=-11%(-20,-2.0)SD(lr)=8.2,17%,19 yrpower=.13/.17/14%y(01)=.006 (.003,.009)r2=.55, p<.022 *tao=-.22, NSSD(sm)=5.1, p<.042,8.8%

pia - 09.04.15 18:04, HCHGGP

116

Lindane, ug/g lipid w., blue mussel

Fladen

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.10

.11

.12

80 85 90 95 00 05

n(tot)=53,n(yrs)=16m=.025 (.018,.035)slope=-9.5%(-12,-6.5)SD(lr)=8.5,5.2%,17 yrpower=.77/.23/12%y(01)=.012 (.009,.016)r2=.77, p<.001 *tao=-.73, p<.001 *SD(sm)=4.6, p<.005,6.1%

Vaderoarna

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.10

.11

.12

80 85 90 95 00 05

n(tot)=50,n(yrs)=15m=.022 (.014,.033)slope=-12%(-16,-8.5)SD(lr)=8.9,6.3%,18 yrpower=.60/.20/13%y(04)=.007 (.005,.010)r2=.81, p<.001 *tao=-.73, p<.001 *SD(sm)=5.5, p<.016,7.6%

Kvadofjarden

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

.10

.11

.12

94 96 98 00 02 04 06


pia - 09.04.29 17:15, HCHGM

117

21 HCB, HexachlorobenzeneUpdated 09.05.31

The use of the highly persistent HCB as a fungicide is banned in the Baltic countries andalthough it may still reach the environment as a by-product of many chlorinating processese.g. pentachlorophenol and vinyl chloride monomer production, we have reasons to expecta decrease in biological samples from the Baltic.

HCB has been analysed in various species, see table below, since 1988. At Harufjärden andLandsort samples from 1987 have been retrospectively analysed.

The detection limit is estimated to approximately 1 ng/g fat weight.



The North Sea Conference (1984, 1987, 1990) that covers all routes of pollution to theNorth Sea, states that the HCB discharges are to be reduced by 50% between 1985 and1995, using 1985 as a base year.

The Minister Declaration from 1988, within HELCOM, calls for a reduction of stableorganic substances by 50% by 1995 with 1987 as a base year.

HCB was withdrawn from market 1980 in Sweden, because of its carcinogenic effects onexperimental animals and it persistence.


In the Baltic proper there are significant decreases in concentrations of HCB in all analysedfish species and in guillemot eggs. Decreasing trends are also found on the Swedish westcoast, in herring and cod from Fladen and blue mussels and eelpout from Väderöarna.

In blue mussels from the Swedish west coast the concentrations are very low. Since the year2000 values are at or below detection limit and hence blue mussels are not considered to bea good matrice for monitoring of HCB´s in this region.

The number of years required to detect an annual change of 5% varied between 14 to 20years for the herring time series.

118

21.1.3 Conclusion

The concentration of HCB in herring, cod, dab and guillemot egg has decreased at a rate ofabout 5-10% per year from the Baltic Proper since 1988. The aim of the North SeaConference and the HELCOM Convention of a 50% reduction of HCB, 1995 with 1985 and1987 respectively as a base year thus seems to be fulfilled.


HCB

< 10

10 - 20

> 20

ng/g lw

TISS - 09.05.05 13:28, HCB

Figure 21.1. Spatial variation in concentration (l.w.) of HCB in herring muscle.

Herring muscle from Landsort and Utlängan in the Baltic Proper represent the highest HCBconcentrations of the herring samples, significantly higher compared to the other sites in thelate eighties. However, since the concentrations have decreased considerably in the samplesfrom the Baltic Proper and the variance from the Bothnian Bay and the Baltic Sea are large,no significant differences can be shown in the estimated concentrations for 2007 in theautumn caught herring from the various sites in the Baltic and the Kattegatt, although theestimated concentrations from 2007 is more than twice as high in the Baltic compared to theSwedish west coast.

The results from eelpout and blue mussel samples from Kvädöfjärden that were analysedfor HCB for the first time 1995, indicate about twice as high concentrations or more in theBaltic compared to the Kattegatt and the Skagerack. This difference is significant for bluemussels and for eelpout when comparing Holmöarna and Väderöarna.

119

21.3 Differences among various species

At some of the sampling sites, specimens of various species are collected within the samearea. HCB is analysed in fish muscle tissue except for cod where the liver is used whereaswhole soft body is analysed in blue mussels. The concentrations found are listed indecreasing order. Differences in geometric mean HCB concentration among the speciessamples from the same area are marked with '>':

Holmöarna: Eelpout(16) > Perch(7)Kvädöfjärden: Eelpout(10) > Perch(6)- Blue mussel(6)Fladen: Cod(9) - Herring(6) >Blue mussel(2.2)Väderöarna: Eelpout(8) - Herring(6) > Blue mussel(1.9)

The lowest concentrations are found in blue mussels whereas the highest are found inguillemot eggs.


Herring caught in the spring show 2-3 times higher HCB-concentrations on a lipid weightbasis compared to samples collected in the autumn.

120

Table 21.1. Estimated geometric mean concentrations of HCB (ug/g lipid weight) in various matrices andsites for the last sampled year.

Matrix age n n yrs year trend last yrHerring msc.Harufj. autumn 3-4 266 19 87-07 -3.5 (-5.5,-1.5)* .015 (.012-.018)Ängskärskl. aut. 3-5 275 18 89-07 -8.4 (-12,-4.7)* .009 (.006-.014)

” spring 259 19 89-07 -6.0 (-8.9, -3.0)* .042 (.031-.058)Landsort 3-5 292 20 87-07 -6.2 (-9.1-3.4)* .019 (.013-.026)Utlängan, aut. 3-4 267 20 88-07 -7.2 (-10,-4.0)* .017 (.012-.024)

” spring 216 19 87-07 -9.5 (-12,-7.2)* .023 (.018-.030)Fladen 2-3 324 20 88-07 -7.4 (-9.4,-5.3)* .006 (.005-.008)Väderöarna 210 11 95-07 .006 (.004-.009)

Cod liverSE Gotland 3-4 152 19 89-07 -7.8 (-11,-5.1)* .018(.013-.024)Fladen 2-3 145 18 89-07 -5.8 (-9.0,-2.6)* .009 (.007-.013)

Perch muscleHolmöarna 112 14 89,95-07 -5.7 (-8.8, -2.7)* .007 (.005-.009)Kvädöfjärden 136 16 84,89-

00,03,07-3.8 (-8.2, -.70)* .006 (.003-.010)

Eelpout muscleHolmöarna 95 11 95-07 -9.7 (-18, -1.1)* .016 (.009-.029)Kvädöfjärden 113 13 95-07 -4.2 (-7.8,-.65)* .010 (.008-.013)Väderöarna 98 13 95-07 .008 (.006-.009)

Dab muscleFladen 3-5 6 6 89-94 .004 (.003-.006)

Flounder mscVäderöarna 4-6 6 6 89-94 .004 (.001-.028)

Blue musselFladen 32 9 88-00# **Väderöarna 31 10 88-00# -7.9 (-16,-.05)* **Kvädöfjärden 58 13 95-07 .005 (.004-.007)

Guillemot eggSt. Karlsö 208 21 79,88-07 -6.5 (-8.4,-4.6)* .62 (.50-.76)

# all values below detection limit during recent years


** no estimated value because of concentrations at or below detection limit

121

HCB, ug/g lipid w., herring muscle

Harufjarden (3-4)

.00

.02

.04

.06

.08

.10

.12

.14

.16

90 95 00 05

n(tot)=266,n(yrs)=19m=.020 (.017,.023)slope=-3.5%(-5.5,-1.5)SD(lr)=5.9,2.9%,14 yrpower=1.0/.38/8.4%y(07)=.015 (.012,.018)r2=.45, p<.002 *tao=-.51, p<.002 *SD(sm)=5.3, NS,7.5%

Angskarsklubb (3-5)

.00

.02

.04

.06

.08

.10

.12

.14

.16

90 95 00 05

n(tot)=275,n(yrs)=18m=.020 (.015,.028)slope=-8.4%(-12,-4.7)SD(lr)=10,5.6%,20 yrpower=.70/.15/15%y(07)=.009 (.006,.014)r2=.60, p<.001 *tao=-.58, p<.001 *SD(sm)=11, NS,16%

Landsort (3-5)

.00

.02

.04

.06

.08

.10

.12

.14

.16

90 95 00 05

n(tot)=292,n(yrs)=20m=.035 (.027,.045)slope=-6.2%(-9.1,-3.4)SD(lr)=11,4.4%,19 yrpower=.90/.17/14%y(07)=.019 (.013,.026)r2=.54, p<.001 *tao=-.53, p<.001 *SD(sm)=10, NS,13%

Utlangan (3-4)

.00

.02

.04

.06

.08

.10

.12

.14

.16

90 95 00 05

n(tot)=267,n(yrs)=20m=.033 (.025,.043)slope=-7.2%(-10,-4.0)SD(lr)=11,4.5%,19 yrpower=.88/.16/15%y(07)=.017 (.012,.024)r2=.56, p<.001 *tao=-.59, p<.001 *SD(sm)=10, NS,13%

pia - 09.04.15 18:13, HCBC

HCB, ug/g lipid w., herring



.00

.05

.10

.15

.20

.25

.30

90 95 00 05

m=.072 (.058,.091)slope=-6.0%(-8.9,-3.0)SD(lr)=13,4.3%,18 yrpower=.92/.20/13%y(07)=.042 (.031,.058)r2=.51, p<.001 *tao=-.53, p<.001 *SD(sm)=15, NS,15%

Karlskrona, spring


.00

.05

.10

.15

.20

.25

.30

90 95 00 05

m=.056 (.041,.075)slope=-9.5%(-12,-7.2)SD(lr)=9.6,3.5%,16 yrpower=.98/.28/10%y(07)=.023 (.018,.030)r2=.82, p<.001 *tao=-.73, p<.001 *SD(sm)=9.1, NS,9.6%

Fladen (2-3)


.00

.05

.10

.15

.20

.25

.30

90 95 00 05

m=.012 (.010,.016)slope=-7.4%(-9.4,-5.3)SD(lr)=5.8,3.0%,15 yrpower=1.0/.33/9.3%y(07)=.006 (.005,.008)r2=.76, p<.001 *tao=-.68, p<.001 *SD(sm)=5.4, NS,8.6%

Vaderoarna

.00

.05

.10

.15

.20

.25

.30

95 00 05

n(tot)=210,n(yrs)=11m=.008 (.006,.010)slope=-4.4%(-11,1.9)SD(lr)=7.1,11%,18 yrpower=.25/.20/13%y(07)=.006 (.004,.009)r2=.22, NStao=-.24, NSSD(sm)=6.5, NS,12%

pia - 09.04.16 13:49, hcbv

122

HCB, ug/g lipid w., cod liver and perch muscle


.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=152,n(yrs)=19m=.036 (.027,.046)slope=-7.8%(-11,-5.1)SD(lr)=9.4,4.0%,17 yrpower=.95/.23/12%y(07)=.018 (.013,.024)r2=.68, p<.001 *tao=-.70, p<.001 *SD(sm)=10, NS,12%

Cod (2-3), Fladen

.00

.02

.04

.06

.08

.10

.12

.14

.16

.18

90 95 00 05

n(tot)=145,n(yrs)=18m=.016 (.012,.020)slope=-5.8%(-9.0,-2.6)SD(lr)=8.4,4.8%,18 yrpower=.84/.19/13%y(07)=.009 (.007,.013)r2=.48, p<.001 *tao=-.52, p<.003 *SD(sm)=7.1, NS,11%

Perch, Holmoarna

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

90 95 00 05

n(tot)=112,n(yrs)=14m=.010 (.008,.013)slope=-5.7%(-8.8,-2.7)SD(lr)=5.4,5.1%,15 yrpower=.79/.34/9.1%y(07)=.007 (.005,.009)r2=.59, p<.001 *tao=-.58, p<.004 *

Perch, Kvadofjarden

.00

.01

.02

.03

.04

.05

.06

.07

.08

.09

85 90 95 00 05

n(tot)=136,n(yrs)=16m=.009 (.007,.011)slope=-3.8%(-8.2,.70)SD(lr)=9.8,7.9%,22 yrpower=.42/.13/18%y(07)=.006 (.003,.010)r2=.19, p<.089tao=-.28, NS

pia - 09.04.16 13:55, HCBGP

HCB, ug/g lipid w., eelpout

Holmoarna

n(tot)=95,n(yrs)=11

.00

.02

.04

.06

.08

.10

.12

.14

94 96 98 00 02 04 06

m=.028 (.019,.041)slope=-9.7%(-18,-1.1)SD(lr)=13,15%,22 yrpower=.16/.13/18%y(07)=.016 (.009,.029)r2=.42, p<.030 *tao=-.49, p<.036 *

Kvadofjarden


.00

.02

.04

.06

.08

.10

.12

.14

94 96 98 00 02 04 06

m=.013 (.011,.015)slope=-4.2%(-7.8,-.65)SD(lr)=5.0,5.1%,14 yrpower=.79/.42/8.0%y(07)=.010 (.008,.013)r2=.38, p<.024 *tao=-.38, p<.067

Vaderoarna

n(tot)=98,n(yrs)=13

.00

.02

.04

.06

.08

.10

.12

.14

94 96 98 00 02 04 06

m=.009 (.008,.010)slope=-2.4%(-4.9,.19)SD(lr)=3.3,3.7%,11 yrpower=.98/.70/5.7%y(07)=.008 (.006,.009)r2=.27, p<.064tao=-.36, p<.088

pia - 09.04.15 18:19, HCBZ

123

HCB, ng/g lipid w., blue mussel

Fladen

0

2

4

6

8

10

12

14

90 95 00 05

n(tot)=32,n(yrs)=9m=2.50 (2.02,3.09)slope=-2.7%(-9.0,3.6)SD(lr)=30,12%,16 yrpower=.21/.28/10%y(00)=2.16 (1.45,3.23)r2=.13, NStao=-.28, NSSD(sm)=28, NS,9.4%

Vaderoarna

0

2

4

6

8

10

12

14

90 95 00 05

n(tot)=31,n(yrs)=10m=2.92 (2.01,4.23)slope=-7.8%(-16,.05)SD(lr)=40,16%,20 yrpower=.14/.14/16%y(00)=1.93 (1.14,3.24)r2=.40, p<.050 *tao=-.36, NSSD(sm)=28, p<.076,11%

Kvadofjarden

0

2

4

6

8

10

12

14

94 96 98 00 02 04 06

n(tot)=58,n(yrs)=13m=6.07 (5.11,7.22)slope=-2.1%(-6.8,2.6)SD(lr)=16,6.7%,16 yrpower=.55/.27/11%y(07)=5.36 (3.85,7.46)r2=.08, NStao=-.18, NSSD(sm)=15, NS,10%

pia - 09.04.29 17:19, HCBM

HCB, ug/g lipid w., guillemot egg, early laidSt. Karlso

0

1

2

3

4

5

6

7

80 85 90 95 00 05

n(tot)=208,n(yrs)=21m=1.15 (.933,1.42)slope=-6.5%(-8.4,-4.6)SD(lr)=166 ,2.7%,14 yrpower=1.0/.38/8.5%y(07)=.619 (.501,.764)r2=.74, p<.001 *tao=-.77, p<.001 *SD(sm)=93.7, p<.001,4.7%

pia - 08.03.12 14:48, hcbu

124

22 PCDD/PCDF, PolychlorinatedDioxins and Dibenzofurans

Updated 09.05.31

Dioxins are unintentionally created during combustion of organic materials. They are highlytoxic and carcinogenic.

Dioxins in guillemot eggs from St. Karlsö have been retrospectively analysed in a timeseries back to 1968. Herring muscle tissue has also been analysed during recent years.

22.1 Conventions aims and restrictions

Dioxins are comprised by the objective of HELCOM’s strategy for hazardous substances,that is to continuously reduce discharges, emissions and losses of hazardous substances,with a goal of their eventual cessation by the year 2020. The ultimate aim is to achieveconcentrations in the environment near background values for naturally occurringsubstances and close to zero for man-made synthetic substances. This objective wasadopted in 1998 and dioxin has been selected as one of the priority substances forimmediate action.

The Stockholm Convention on Persistent Organic Pollutants (POPs) is an internationalagreement, requiring measures for reducing or preventing releases of dioxins to theenvironment



The dioxin content of fat fish from the Baltic often exceeds the prescribed maximum limit(4 WHO-PCDD/F pg/g or 8 WHO-PCDD/F-PCBTEQ pg/g fresh weight) within theEuropean Union, and therefore Sweden and Finland are currently only allowed to sell on thedomestic market or to non member states (EC 2375/2001, EC 201/2002, EC 199/2006, EC1881/2006). However, the TEQ levels in herring from the reference sites in thisinvestigation do not exceed the prescribed maximum.

In guillemot eggs significant decreasing trends are observed for TCDD, TCDF and TCDD-equivalents during the whole period. However there is a difference over time betweenPCDD and PCDF. PCDF does not show the same decrasing trend during the recent 10years as PCDD. This might explain the ceased trend for TCDD-equivalents during the last20 years. The number of years required to detect an annual change of 5% varied between 12and 18 years in the time series of guillemot.

125

There are no significant changes in concentration over time in herring muscle. The numberof years required to detect an annual change of 5% varied between 17 and 18 years for thesetime series.


TCDD-eqv

< 15

15 - 30

> 30

pg/g lw

TISS - 09.05.05 14:14, TCDDEQV

Figure 22.1. Spatial variation in concentration (l.w.) of TCDD-equivalents in herring muscle.

The TCDD-eqv in figure 22.1 (only one year is presented for the new sampling sites) areelevated in herring muscle from Harufjärden(Bothnian Bay) and Gaviksfjärden (BothnianSea) compared to localities in the Baltic Proper and at the Swedish west coast

Table 22.1. Geometric mean concentrations of TCDD-eqv. (pg/g lipid weight) in various matrices and sitesduring 1988/1990-2007 and estimated mean concentration 2007.

Matrix age n tot n yrs year trend Mean (last year iftrend)

Herring msc.Harufj. autumn 133 17 90-07 4.1 (-.50, 7.7)* 43 (31-61)Utlängan 179 18 88, 90, 92-

0727 (21-36)

Fladen 134 18 90-07 8.9 (6.4-12)

Guillemot eggSt. Karlsö 162 37 68-07 -3.0 (-3.7, -2.3)* .83 (.72-0.96)

126


Table 22.2. Geometric mean concentrations of TCDD-eqv. (pg/g fresh weight) in various matrices and sitesduring 1988/1990-2007 and estimated mean concentration 2007.


Herring msc.Harufj. autumn 133 17 90-07 .88 (.61-.1.3)Utlängan 173 17 90, 92-07 .71 (.50-1.0)Fladen 134 18 90-07 .44 (.31-.62)

TCDD-equivalents, pg/g fat, herring muscle

Harufjarden

0

10

20

30

40

50

60

70

80

90

88 92 96 00 04

n(tot)=133,n(yrs)=17m=31.1 (25.3,38.2)slope=4.1%(.50,7.7)SD(lr)=10,5.3%,18 yrpower=.76/.19/13%y(07)=43.3 (30.7,61.0)r2=.28, p<.027 *tao=.38, p<.032 *SD(sm)=9.7, NS,12%

Utlangan

0

10

20

30

40

50

60

70

80

90

88 92 96 00 04

n(tot)=179,n(yrs)=18m=27.9 (24.3,32.1)slope=-.33%(-3.0,2.3)SD(lr)=8.7,4.0%,16 yrpower=.95/.26/11%y(07)=27.1 (20.7,35.6)r2=.00, NStao=.07, NSSD(sm)=7.9, NS,9.6%

Fladen

0

10

20

30

40

50

60

70

80

90

88 92 96 00 04

n(tot)=134,n(yrs)=18m=8.94 (7.58,10.5)slope=-.12%(-3.4,3.2)SD(lr)=16,4.7%,18 yrpower=.85/.20/13%y(07)= 8.9 ( 6.4,12.3)r2=.00, NStao=-.07, NSSD(sm)=14, NS,12%

pia - 09.03.25 19:16, tcddec

127

TCDD-equivalents, pg/g fresh wt, herring muscle

Harufjarden

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

88 90 92 94 96 98 00 02 04 06

n(tot)=133,n(yrs)=17m=.803 (.661,.974)slope=1.2%(-2.8,5.2)SD(lr)=174,5.8%,19 yrpower=.67/.17/14%y(07)= .88 ( .61,1.29)r2=.03, NStao=.09, NSSD(sm)=189, NS,16%

Utlangan

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

88 90 92 94 96 98 00 02 04 06

n(tot)=173,n(yrs)=17m=.705 (.589,.843)slope=.07%(-3.7,3.8)SD(lr)=103,5.5%,18 yrpower=.73/.18/13%y(07)= .71 ( .50,1.01)r2=.00, NStao=.04, NSSD(sm)=87, NS,11%

Fladen

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

88 90 92 94 96 98 00 02 04 06

n(tot)=134,n(yrs)=18m=.389 (.326,.463)slope=1.5%(-2.0,4.9)SD(lr)=37,4.9%,18 yrpower=.83/.19/13%y(07)=.440 (.313,.618)r2=.05, NStao=.27, NSSD(sm)=35, NS,12%

pia - 09.03.25 19:16, tcddecw

PCDD/PCDF in guillemot eggTCDD, pg/g fat


0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

70 75 80 85 90 95 00 05

m=272 (218 ,339 )slope=-5.3%(-5.8,-4.7)SD(lr)=3.0,.90%,12 yrpower=1.0/.62/6.2%y(07)= 95 ( 84, 107)r2=.93, p<.001 *tao=-.86, p<.001 *SD(sm)=1.8, p<.001,3.7%slope=-9.4%(-13,-5.2)SD(lr)=1.8,5.8%,8 yrpower=.69/1.0/3.1%r2=.87, p<.003 *

TCDF, pg/g fat


0

20

40

60

80

100

120

140

160

70 75 80 85 90 95 00 05

m=51.2 (44.9,58.3)slope=-1.5%(-2.6,-.49)SD(lr)=8.4,1.8%,17 yrpower=1.0/.21/12%y(07)=37.6 (29.6,47.8)r2=.22, p<.005 *tao=-.33, p<.007 *SD(sm)=5.0, p<.001,7.1%slope=-2.7%(-14,9.0)SD(lr)=6.5,17%,14 yrpower=.14/.36/8.8%r2=.06, NS

TCDD-eqvivalents, ng/g fat


0

1

2

3

4

5

6

70 75 80 85 90 95 00 05

m=1.45 (1.27,1.66)slope=-3.0%(-3.7,-2.3)SD(lr)=59,1.0%,14 yrpower=1.0/.41/8.1%y(07)=.827 (.715,.958)r2=.70, p<.001 *tao=-.62, p<.001 *SD(sm)=36, p<.001,4.9%slope=-.91%(-5.5,3.7)SD(lr)=202,6.5%,12 yrpower=.58/.58/6.5%r2=.03, NS

pia - 09.04.01 11:06, DXU

128

23 Polybrominated flame retardantsUpdated 09.05.31

Polybrominated flame retardants in guillemot eggs from St. Karlsö have beenretrospectively analysed in a time series back to 1968. Herring muscle tissue has also beenanalysed during recent years.



Significant increasing concentrations of BDE-47, BDE-99 and BDE-100, in guillemot eggs,from the late sixties until the early nineties are followed by decreasing values during therecent period.

Decreasing concentrations of BDE-47 can also be observed in herring from Ängskärsklubband Väderöarna and in cod and herring from Fladen.For HBCD a significant increasing trend is shown in guillemot eggs. The concentrations ofHBCD are increasing in guillemot eggs with about 3% per year. In herring on the contraryHBCD is decreasing at Utlängan (12% per year) in the Baltic Proper and at Fladen (17% peryear) and Väderöarna (16% per year) at the Swedish west coast.

The number of years required to detect an annual change of 5%, in the concentration ofBDE-47, is 11 to 19 years for herring and cod (except for herring caught at Ängskärsklubbin spring) and for HBCD 15 to 24 years,

129


HBCD

< 10

10 - 20

> 20

ng/g lw

TISS - 09.05.05 14:30, HBCD

Figure 23.1. Spatial variation in concentration (l.w.) of HBCD in herring muscle.

Figure 23.1 indicate eleveated concentrations of HBCD (lipid weight) at the sampling sitesin the south Baltic Proper and at Gaviksfjärden in the Bothnian Sea (only one year ispresented for the new sampling sites). The figure 23.2 and the time series for herringindicate elevated concentrations of some of the substances at Karlskrona in the southernBaltic Proper. In general the PBDE’s and HBCD seem to be more evenly distributed amongsites compared to e.g. PCB.

Table 23.1. Geometric mean concentrations of BDE-47 (ng/g lipid weight) in various matrices and sitesduring monitoring period and estimated mean concentration 2007.


Herring msc.Harufj. 107 9 99-07 5.0 (2.8-8.9)Ängskärsklubbautum

108 9 99-07 -11 (-19,-3.1)* 3.8 (2.6-5.5)

Ängskärsklubbspring

57 6 02-07 15 (8.3-28)

Landsort 103 9 99-07 -11 (-20,-1.7)* 4.5 (2.9-6.7)Utlänganautumn

101 9 99-07 -8.4 (-16,.57 ) 6.3 (4.4-9.2)

Utlängan spring 48 5 03-07 13 (8.3-21)Fladen 108 9 99-07 -18 (-23,-14)* 1.9 (1.5-2.4)Väderöarna 152 8 99-07 -18 (-27,-9.7)* 2.0 (1.3-3.1)

Cod liverSE Gotland 87 9 99-07 19 (14-28)Fladen 86 9 99-07 -19 (-30,-8.3)* 12 (7.1-20)Guillemot eggSt. Karlsö 187 33 68-07 59 (30-120)* significant trend, p < 0.05

130

Table 23.2. Geometric mean concentrations of HBCD (ng/g lipid weight) in various matrices and sites duringmonitoring period and estimated mean concentration 2007.


Herring msc.Harufj. 107 9 99-07 10 (4.6-23)Ängskärsklubbautum

105 9 99-07 3.5 (1.7-7.3)

Ängskärsklubbspring

57 6 02-07 25 (9.7-63)

Landsort 103 9 99-07 13 (8.8-19)Utlänganautumn

100 9 99-07 12 (-25,.46) 9.5 (5.2-185)

Utlängan spring 56 6 02-07 30 (14-68)

Fladen 105 9 99-07 -17 (-26,-6.9) 3.1 (2.0-4.9)

Väderöarna 143 8 02-07 -16 (-27,-4.8) 2.7 (1.5-4.7)

Cod liverSE Gotland 86 9 99-07 19 (9.1-39)Fladen 50 6 99-07 5.5 (2.3-13)Guillemot eggSt. Karlsö 197 34 68-07 3.0 (1.9,4.0)* 170 (140-210)* significant trend, p < 0.05

Brominated contaminants in Guillemot egg, ng/g lipid w.

BDE-47


0

200

400

600

800

1000

1200

1400

1600

1800

65 75 85 95 05

SD(sm)=6.1, p<.001,12%slope=-6.4%(-19,6.3)SD(lr)=11,23%,22 yrpower=.10/.12/19%y(07)= 59 ( 30, 118)r2=.17, NSslope=16%(10,21)SD(lr)=10,10%,25 yrpower=.28/.10/23%y(88)= 1502 ( 830, 2718)r2=.73, p<.001 *tao=.67, p<.001 *

BDE-100


0

20

40

60

80

100

120

140

160

180

65 75 85 95 05

SD(sm)=14, p<.001,17%slope=-18%(-39,3.2)SD(lr)=28,37%,22 yrpower=.07/.12/18%y(07)=2.84 (1.12,7.25)r2=.49, p<.081slope=18%(11,25)SD(lr)=24,13%,30 yrpower=.18/.08/31%y(88)= 121 ( 56, 259)r2=.67, p<.001 *

BDE-99


0

40

80

120

160

200

240

280

320

65 75 85 95 05

SD(sm)=11, p<.001,14%slope=-3.5%(-8.0,.93)SD(lr)=7.5,7.5%,12 yrpower=.47/.62/6.2%y(07)= 8.4 ( 6.6,10.7)r2=.33, NSslope=19%(12,27)SD(lr)=21,14%,31 yrpower=.16/.07/34%y(88)= 312 ( 136, 712)r2=.68, p<.001 *

HBCD


0

40

80

120

160

200

240

280

65 75 85 95 05

m=99.4 (84.1,117 )slope=3.0%(1.9,4.0)SD(lr)=7.4,1.8%,18 yrpower=1.0/.20/13%y(07)= 169 ( 135, 211)r2=.51, p<.001 *tao=.57, p<.001 *SD(sm)=4.8, p<.001,8.1%slope=4.0%(-.85,8.8)SD(lr)=3.8,6.9%,12 yrpower=.53/.53/6.9%r2=.31, p<.092

pia - 09.03.25 18:39, BRUL2

131

PBDE, ng/g lipid w., herring muscle from different sampling sitesBDE-47

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

0 1 2 3 4 5 6 7

m= 9.9 (7.72,12.7)

BDE-99

0

1

2

3

4

5

6

7

8

9

10

11

0 1 2 3 4 5 6 7

m=2.69 (1.74,4.15)

BDE-100

.0

.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

0 1 2 3 4 5 6 7

m=1.85 (1.44,2.38)

BDE-153

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

0 1 2 3 4 5 6 7

m=.370 (.258,.529)

BDE-154

.0

.2

.4

.6

.8

1.0

1.2

1.4

1.6

1.8

0 1 2 3 4 5 6 7

m=.434 (.324,.580)

HBCD

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

32

34

36

38

0 1 2 3 4 5 6 7

m=10.4 (6.35,17.2)

pia - 06.03.28 16:32, bdec2

Figure 23.2: Spatial variation of some polybrominated flame retardants. 1=Harufjärden (Bothnian Bay),2=Ängskärsklubb (S. Gulf of Bothnia), 3=Landsort (N. Baltic Proper), 4=Karlskrona (S.Baltic Proper),6=Fladen (Kattegatt), 7=Väderöarna (Skagerack)

BDE-47, ng/g lipid w., herring muscle

Harufjarden

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=107,n(yrs)=9m=6.60 (4.80,9.07)slope=-6.8%(-19,5.3)SD(lr)=21,18%,19 yrpower=.13/.16/15%y(07)=5.03 (2.83,8.93)r2=.20, NStao=-.22, NSSD(sm)=22, NS,16%

Angskarsklubb (3-5)

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=108,n(yrs)=9m=5.86 (4.34,7.91)slope=-11%(-19,-3.1)SD(lr)=15,12%,15 yrpower=.23/.31/9.6%y(07)=3.76 (2.57,5.51)r2=.60, p<.014 *tao=-.56, p<.037 *SD(sm)=16, NS,11%

Landsort (3-5)

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=103,n(yrs)=9m=6.96 (5.08, 9.5)slope=-11%(-20,-1.7)SD(lr)=15,13%,16 yrpower=.19/.25/11%y(07)=4.50 (2.91,6.96)r2=.53, p<.025 *tao=-.56, p<.037 *SD(sm)=17, NS,12%

Utlangan (3-4)

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=101,n(yrs)=9m=8.86 (6.86,11.4)slope=-8.4%(-16,-.57)SD(lr)=12,11%,15 yrpower=.24/.32/9.4%y(07)=6.33 (4.36,9.19)r2=.48, p<.038 *tao=-.44, p<.095SD(sm)=7.0, p<.016,5.5%

pia - 09.03.25 18:44, bde47c

132

BDE-47, ng/g lipid w., herring muscle

Fladen

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=108,n(yrs)=9m=3.97 (2.67,5.92)slope=-18%(-23,-14)SD(lr)=11,6.4%,11 yrpower=.59/.75/5.3%y(07)=1.91 (1.54,2.38)r2=.93, p<.001 *tao=-.78, p<.004 *SD(sm)=12, NS,5.8%

Vaderoarna

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=152,n(yrs)=8m=4.48 (2.84,7.07)slope=-18%(-27,-9.7)SD(lr)=17,14%,15 yrpower=.18/.33/9.2%y(07)=2.00 (1.29,3.10)r2=.82, p<.002 *tao=-.79, p<.006 *SD(sm)=20, NS,11%

Angskarsklubb spring

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=57,n(yrs)=6m=15.2 (8.31,27.6)slope=-7.6%(-49,33)SD(lr)=23,74%,26 yrpower=.06/.09/24%y(07)=12.5 ( 3.6,43.5)r2=.06, NStao=-.07, NSSD(sm)=25, NS,27%

Karlskrona, spring

0

4

8

12

16

20

24

28

98 00 02 04 06

0

4

8

12

16

20

24

28

n(tot)=48,n(yrs)=5m=13.2 (8.28,21.1)slope=-19%(-45,7.1)SD(lr)=10,42%,15 yrpower=.07/.31/9.5%y(07)= 9.0 ( 4.8,17.1)r2=.64, NStao=-.60, NSSD(sm)=11, NS,10%

pia - 09.03.25 18:45, bde47v

BDE-47, ng/g lipid w., cod liver

SE Gotland

0

10

20

30

40

50

60

70

80

90

98 00 02 04 06

n(tot)=87,n(yrs)=9m=19.3 (16.2,22.9)slope=.10%(-7.3,7.4)SD(lr)=8.1,11%,14 yrpower=.27/.36/8.8%y(07)=19.4 (13.6,27.5)r2=.00, NStao=-.11, NSSD(sm)=10, p<.001,11%

Fladen

0

10

20

30

40

50

60

70

80

90

98 00 02 04 06

n(tot)=86,n(yrs)=9m=25.8 (15.9,41.8)slope=-19%(-30,-8.3)SD(lr)=11,16%,18 yrpower=.14/.18/13%y(07)=11.9 ( 7.1,20.1)r2=.71, p<.004 *tao=-.72, p<.007 *SD(sm)=12, NS,15%

pia - 09.04.16 14:46, bde47g

133

HBCD, ng/g lipid w., herring muscle

Harufjarden

0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=107,n(yrs)=9m=8.20 (5.40,12.5)slope=5.7%(-11,23)SD(lr)=26,26%,24 yrpower=.09/.10/21%y(07)=10.3 ( 4.6,23.2)r2=.08, NStao=.11, NSSD(sm)=23, NS,19%

Angskarsklubb (3-5)

0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=105,n(yrs)=9m=4.96 (3.30,7.46)slope=-8.8%(-24,6.6)SD(lr)=32,24%,23 yrpower=.10/.12/19%y(07)=3.49 (1.67,7.26)r2=.21, NStao=-.28, NSSD(sm)=40, NS,25%

Landsort (3-5)

0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=103,n(yrs)=9m=12.5 (10.3,15.1)slope=.91%(-7.1,9.0)SD(lr)=10,12%,15 yrpower=.23/.31/9.7%y(07)=13.0 ( 8.8,19.0)r2=.01, NStao=.17, NSSD(sm)=11, NS,10%

Utlangan (3-4)

0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=100,n(yrs)=9m=15.6 (10.5,23.3)slope=-12%(-25,.46)SD(lr)=15,19%,20 yrpower=.12/.15/16%y(07)= 9.5 ( 5.2,17.5)r2=.43, p<.055tao=-.56, p<.037 *SD(sm)=16, NS,16%

pia - 09.03.25 18:53, hbcdc

HBCD, ug/g lipid w., herring muscle

Fladen

0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=105,n(yrs)=9m=5.99 (3.96,9.07)slope=-17%(-26,-6.9)SD(lr)=18,14%,17 yrpower=.17/.23/12%y(07)=3.09 (1.96,4.89)r2=.70, p<.005 *tao=-.56, p<.037 *SD(sm)=20, NS,14%

Vaderoarna

0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=143,n(yrs)=8m=5.34 (3.46,8.26)slope=-16%(-27,-4.8)SD(lr)=19,18%,17 yrpower=.13/.22/12%y(07)=2.66 (1.51,4.66)r2=.67, p<.013 *tao=-.71, p<.013 *SD(sm)=26, NS,16%


0

5

10

15

20

25

30

35

40

45

98 00 02 04 06

n(tot)=57,n(yrs)=6m=20.4 (12.8,32.4)slope=7.9%(-23,39)SD(lr)=15,52%,22 yrpower=.06/.13/18%y(07)=24.8 ( 9.7,63.3)r2=.11, NStao=.33, NSSD(sm)=18, NS,21%

Karlskrona, spring

0

10

20

30

40

50

60

70

80

90

98 00 02 04 06

n(tot)=56,n(yrs)=6m=35.0 (23.6,51.9)slope=-5.9%(-32,21)SD(lr)=11,43%,20 yrpower=.07/.16/15%y(07)=30.2 (13.5,67.5)r2=.09, NStao=-.20, NSSD(sm)=9.7, p<.082,13%

pia - 09.05.04 11:26, hbcdv

134

HBCD in Guillemot egg, ng/g lipid w.


0

50

100

150

200

250

70 75 80 85 90 95 00 05

0

50

100

150

200

250

slope=3.0%(1.9,4.0)SD(lr)=7.4,1.8%,18 yrpower=1.0/.20/13%y(07)= 169 ( 135, 211)r2=.51, p<.001 *tao=.57, p<.001 *SD(sm)=4.8, p<.001,8.1%

pia - 09.03.30 13:29, HBCDU

135

24 PAHs, PolyaromaticHydrocarbons

Updated 09.05.31

Polyaromatic Hydrocarbons have been retrospectively analysed in blue mussels fromKvädöfjärden in the Baltic and Fladen and Väderöarna at the Swedish west coast in timeseries from 1987 to 2003, 1987 to 2003 and 1984 to 2003, respectively. PAHs are since2003 analysed on a yearly basis from these three blue mussel sampling sites. The PAHsanalysed are: Naphthalene, Acenaphtene, Fluorene, Phenantrene, Antracene, Flouranthene,Pyrene, Benso(a)antracene, Chrysene, Benso(b)fluoranthene, Benso(k)fluoranthene,Benso(a)pyrene, Dibenso(a,h)antracene, Benso(g,h,i)perylene and Indeno(1,2,3-cd)pyrene.

The source of PAHs is either pyroliytic or petrogenic and can be evaluated by moleculeindexes and is based on concentration relationships between individual PAHs (Pikkarainen2004). Metabolic capacity of the species sampled has to be considered.



All PAHs analysed (except acenapthene, which rarely was found over the detection limit)are presented as time series below. Significant decreasing trends are found in the time seriesfor Fluoranthene and Pyrene (Väderöarna) and Naphtalene (Kvädöfjärden). A significantincreasing trend is shown for Flouranthene at Kvädöfjärden.

The number of years required to detect an annual change of 5%, in the concentration variesa lot with type of PAH and sampling site. Generally the statistical power to detect trends arelow compared to other contaminants.

Some of the PAHs (eg. Anthracene and Fluoranthene) are extremely high in concentrationcertain years compared to the average concentrations. These results could possibly beconsidered to be true outliers. The power and number of years required to detect a trendwould improve if these outliers were excluded.

136


sPAH

< 50

50 - 100

> 100

ng/g dw

TISS - 09.05.27 14:24, sPAH

Figure 24.1. Spatial variation in concentration (d.w.) of sPAH in blue mussle soft body.

Blue mussel soft body from Kvädöfjärden in the Baltic Proper represent the highest sPAHconcentration of the blue mussel samples (figure 24.1). The retrospective studies show thatthe PAHs are not all systematically higher at Kvädöfjärden. Flouranthene and Pyrene forexample show higher concentrations at Väderöarna.

137

sPAH, ng/g dry w., blue mussel

Fladen

0

40

80

120

160

200

240

280

80 85 90 95 00 05

n(tot)=14,n(yrs)=14m=44.3 (27.9,70.4)slope=-1.6%(-9.2,6.0)SD(lr)=22,18%,31 yrpower=.12/.07/34%y(07)=38.7 (17.3,86.7)r2=.02, NStao=-.21, NSSD(sm)=22, NS,34%

Vaderoarna

0

40

80

120

160

200

240

280

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=69.5 (49.1,98.3)slope=-3.4%(-8.2,1.4)SD(lr)=15,11%,26 yrpower=.26/.09/24%y(07)=50.8 (29.4,88.0)r2=.14, NStao=-.16, NSSD(sm)=12, p<.090,20%

Kvadofjarden

0

40

80

120

160

200

240

280

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=110 (86.0,141 )slope=.08%(-4.0,4.2)SD(lr)=10,8.2%,22 yrpower=.40/.12/18%y(07)= 111 ( 66, 187)r2=.00, NStao=-.12, NSSD(sm)=11, NS,19%

pia - 09.05.27 13:46, sPAHM

Anthracene, ng/g dry w., blue mussel

Fladen

0

1

2

3

4

5

6

7

8

80 85 90 95 00 05

0

5

n(tot)=16,n(yrs)=14m=.223 (.120,.414)slope=-4.3%(-14,5.5)SD(lr)=72,24%,37 yrpower=.09/.06/45%y(07)=.154 (.054,.438)r2=.07, NStao=-.23, NSSD(sm)=65, NS,40%

Vaderoarna

0

1

2

3

4

5

6

7

8

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=.433 (.330,.569)slope=-1.6%(-5.6,2.4)SD(lr)=62,8.7%,23 yrpower=.36/.11/20%y(07)=.375 (.238,.590)r2=.05, NStao=-.06, NSSD(sm)=44, p<.020,14%

Kvadofjarden

0

1

2

3

4

5

6

7

8

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=.365 (.206,.647)slope=3.4%(-5.8,13)SD(lr)=108,19%,37 yrpower=.11/.06/46%y(07)= .53 ( .17,1.70)r2=.04, NStao=-.08, NSSD(sm)=117, p<.020,51%

pia - 09.05.27 13:33, ANT

138

Benzo(a)anthracene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

25

30

80 85 90 95 00 05

n(tot)=13,n(yrs)=12m=3.07 (2.21,4.29)slope=.73%(-5.5,7.0)SD(lr)=49,15%,24 yrpower=.15/.11/21%y(07)=3.24 (1.84,5.70)r2=.01, NStao=.06, NSSD(sm)=50, NS,22%

Vaderoarna

0

5

10

15

20

25

30

80 85 90 95 00 05


Kvadofjarden

0

5

10

15

20

25

30

80 84 88 92 96 00 04

n(tot)=14,n(yrs)=14m=5.94 (3.96,8.92)slope=3.8%(-3.1,11)SD(lr)=39,15%,28 yrpower=.16/.08/27%y(07)= 9.0 ( 3.8,21.4)r2=.11, NStao=.03, NSSD(sm)=42, NS,29%

pia - 09.05.27 13:27, BAA

Benzo(a)pyrene, ng/g dry w., blue mussel

Fladen

0

2

4

6

8

10

12

14

16

18

20

80 85 90 95 00 05

n(tot)=15,n(yrs)=13m=.580 (.326,1.03)slope=****%(-11,8.9)SD(lr)=182,25%,35 yrpower=.09/.07/41%y(06)= .53 ( .19,1.47)r2=.00, NStao=-.15, NSSD(sm)=189, NS,43%

Vaderoarna

0

2

4

6

8

10

12

14

16

18

20

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=1.21 (.715,2.05)slope=-1.5%(-9.4,6.3)SD(lr)=529,18%,35 yrpower=.12/.06/43%y(07)=1.05 ( .43,2.58)r2=.01, NStao=-.04, NSSD(sm)=481, NS,38%

Kvadofjarden

0

2

4

6

8

10

12

14

16

18

20

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=4.14 (2.91,5.88)slope=1.8%(-3.9,7.6)SD(lr)=47,12%,27 yrpower=.23/.09/27%y(07)= 5.0 ( 2.5,10.4)r2=.03, NStao=-.08, NSSD(sm)=49, NS,27%

pia - 09.05.27 13:40, BAP

139

Benzo(b)fluoranthene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

25

30

80 85 90 95 00 05

n(tot)=16,n(yrs)=14m=3.06 (1.88,4.97)slope=.94%(-7.1,8.9)SD(lr)=78,19%,32 yrpower=.12/.07/36%y(07)=3.32 (1.42,7.75)r2=.01, NStao=-.05, NSSD(sm)=81, NS,37%

Vaderoarna

0

5

10

15

20

25

30

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=5.35 (3.36,8.51)slope=-3.2%(-9.9,3.4)SD(lr)=52,15%,32 yrpower=.15/.07/35%y(07)=3.99 (1.86,8.56)r2=.07, NStao=-.08, NSSD(sm)=41, p<.058,28%

Kvadofjarden

0

5

10

15

20

25

30

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=10.9 (8.08,14.8)slope=1.2%(-3.7,6.2)SD(lr)=24,9.9%,25 yrpower=.29/.10/23%y(07)=12.5 ( 6.7,23.4)r2=.02, NStao=.03, NSSD(sm)=23, NS,22%

pia - 09.05.27 13:38, BBF

Benzo(g,h,i)perylene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

25

30

80 85 90 95 00 05

n(tot)=15,n(yrs)=13m=1.53 (.932,2.51)slope=-.28%(-8.8,8.3)SD(lr)=202,21%,32 yrpower=.10/.07/35%y(06)=1.49 ( .63,3.57)r2=.00, NStao=-.18, NSSD(sm)=199, NS,34%

Vaderoarna

0

5

10

15

20

25

30

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=2.82 (1.94,4.09)slope=.80%(-4.8,6.4)SD(lr)=70,12%,28 yrpower=.20/.08/29%y(07)=3.03 (1.60,5.72)r2=.01, NStao=.11, NSSD(sm)=65, NS,26%

Kvadofjarden

0

5

10

15

20

25

30

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=11.2 (8.69,14.5)slope=-1.0%(-5.2,3.2)SD(lr)=20,8.3%,22 yrpower=.38/.12/19%y(07)=10.0 ( 5.9,17.0)r2=.02, NStao=-.08, NSSD(sm)=20, NS,19%

pia - 09.05.27 13:42, BGHIP

140

Benzo(k)fluoranthene, ng/g dry w., blue mussel

Fladen

0

2

4

6

8

10

12

14

80 85 90 95 00 05

0

5

10

15n(tot)=16,n(yrs)=14m=1.16 (.713,1.90)slope=.73%(-7.4,8.8)SD(lr)=580,19%,32 yrpower=.11/.07/36%y(07)=1.24 ( .52,2.92)r2=.00, NStao=-.05, NSSD(sm)=595, NS,37%

Vaderoarna

0

2

4

6

8

10

12

14

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=1.87 (1.15,3.02)slope=-2.4%(-9.4,4.7)SD(lr)=147,16%,33 yrpower=.14/.07/38%y(07)=1.51 ( .67,3.37)r2=.04, NStao=-.08, NSSD(sm)=126, NS,32%

Kvadofjarden

0

2

4

6

8

10

12

14

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=5.63 (4.26,7.45)slope=-.42%(-5.0,4.2)SD(lr)=31,9.2%,24 yrpower=.33/.11/21%y(07)=5.38 (3.01,9.62)r2=.00, NStao=-.07, NSSD(sm)=32, NS,21%

pia - 09.05.27 13:40, BKF

Chrysene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

25

30

35

40

80 85 90 95 00 05


Vaderoarna

0

5

10

15

20

25

30

35

40

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=7.07 (4.37,11.4)slope=-5.2%(-12,1.4)SD(lr)=44,15%,32 yrpower=.16/.07/35%y(07)=4.43 (2.09,9.37)r2=.17, NStao=-.26, NSSD(sm)=36, p<.079,28%

Kvadofjarden

0

5

10

15

20

25

30

35

40

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=9.16 (6.85,12.3)slope=-1.7%(-6.5,3.0)SD(lr)=25,9.4%,24 yrpower=.32/.10/21%y(07)= 7.6 ( 4.2,13.7)r2=.04, NStao=-.13, NSSD(sm)=24, NS,21%

pia - 09.05.27 13:37, CHR

141

Dibenzo(a,h)anthracene, ng/g dry w., blue mussel

Fladen

.0

.5

1.0

1.5

2.0

2.5

3.0

80 85 90 95 00 05

0

n(tot)=7,n(yrs)=6m=.292 (.093,.911)slope=.48%(-19,20)SD(lr)=98,>99%,39 yrpower=.05/.06/53%y(06)= .30 ( .04,2.39)r2=.00, NStao=.07, NSSD(sm)=120, NS,68%

Vaderoarna

.0

.5

1.0

1.5

2.0

2.5

3.0

80 85 90 95 00 05

n(tot)=11,n(yrs)=11m=.427 (.281,.650)slope=-.51%(-6.8,5.8)SD(lr)=77,22%,27 yrpower=.10/.09/26%y(07)=.408 (.197,.846)r2=.00, NStao=.00, NSSD(sm)=82, NS,28%

Kvadofjarden

.0

.5

1.0

1.5

2.0

2.5

3.0

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=.958 (.708,1.30)slope=-.35%(-5.4,4.6)SD(lr)=1371,10%,25 yrpower=.29/.10/23%y(07)= .92 ( .49,1.73)r2=.00, NStao=-.03, NSSD(sm)=1358, NS,23%

pia - 09.05.27 13:41, DBAHA

Fluorene, ng/g dry w., blue mussel

Fladen

0

1

2

3

4

5

6

7

8

80 85 90 95 00 05

0

5

n(tot)=16,n(yrs)=14m=1.21 (.706,2.08)slope=-.72%(-9.6,8.2)SD(lr)=508,22%,34 yrpower=.10/.07/40%y(07)=1.14 ( .44,2.94)r2=.00, NStao=-.12, NSSD(sm)=474, NS,37%

Vaderoarna

0

1

2

3

4

5

6

7

8

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=1.97 (1.49,2.60)slope=-1.9%(-5.9,2.1)SD(lr)=77,8.8%,23 yrpower=.35/.11/20%y(07)=1.66 (1.05,2.63)r2=.07, NStao=-.06, NSSD(sm)=74, NS,19%

Kvadofjarden

0

1

2

3

4

5

6

7

8

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=1.39 (.940,2.05)slope=3.2%(-3.0,9.4)SD(lr)=221,12%,28 yrpower=.20/.08/29%y(07)=1.96 ( .90,4.26)r2=.08, NStao=.05, NSSD(sm)=216, NS,28%

pia - 09.05.27 13:32, FLE

142

Fluoranthene, ng/g dry w., blue mussel

Fladen

0

10

20

30

40

50

60

70

80

80 85 90 95 00 05

n(tot)=16,n(yrs)=14m=6.77 (3.79,12.1)slope=-1.6%(-11,7.9)SD(lr)=54,23%,36 yrpower=.09/.06/44%y(07)= 5.9 ( 2.1,16.2)r2=.01, NStao=-.16, NSSD(sm)=55, NS,44%

Vaderoarna

0

10

20

30

40

50

60

70

80

80 85 90 95 00 05

n(tot)=15,n(yrs)=15m=18.0 (12.2,26.6)slope=-4.4%(-9.5,.78)SD(lr)=22,12%,27 yrpower=.20/.09/25%y(07)=11.9 ( 6.5,21.8)r2=.21, p<.087tao=-.15, NSSD(sm)=17, p<.034,18%

Kvadofjarden

0

10

20

30

40

50

60

70

80

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=12.1 (8.03,18.3)slope=5.3%(-.83,11)SD(lr)=29,12%,28 yrpower=.20/.08/28%y(07)=21.5 (10.0,46.2)r2=.20, p<.082tao=.30, NSSD(sm)=29, NS,29%

pia - 09.05.27 13:35, FLU

Indeno(1,2,3-cd)pyrene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

80 85 90 95 00 05

n(tot)=13,n(yrs)=13m=1.12 (.669,1.89)slope=1.5%(-7.4,10)SD(lr)=760,22%,32 yrpower=.10/.07/36%y(06)=1.27 ( .51,3.15)r2=.01, NStao=.05, NSSD(sm)=750, NS,36%

Vaderoarna

0

5

10

15

20

80 85 90 95 00 05

n(tot)=13,n(yrs)=13m=2.16 (1.40,3.34)slope=3.7%(-2.2,9.6)SD(lr)=90,17%,28 yrpower=.13/.08/27%y(07)=3.16 (1.51,6.60)r2=.15, NStao=.30, NSSD(sm)=95, NS,29%

Kvadofjarden

0

5

10

15

20

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=8.18 (6.22,10.8)slope=.07%(-4.5,4.6)SD(lr)=25,9.0%,23 yrpower=.34/.11/21%y(07)= 8.2 ( 4.7,14.6)r2=.00, NStao=-.08, NSSD(sm)=25, NS,20%

pia - 09.05.27 13:44, ICDP

143

Naphtalene, ng/g dry w., blue mussel

Fladen

0

10

20

30

40

50

60

70

80

90

100

80 85 90 95 00 05

n(tot)=16,n(yrs)=14m=2.54 (1.67,3.87)slope=-3.0%(-9.6,3.7)SD(lr)=78,16%,28 yrpower=.15/.08/29%y(07)=1.98 ( .97,4.01)r2=.07, NStao=-.05, NSSD(sm)=75, NS,28%

Vaderoarna

0

10

20

30

40

50

60

70

80

90

100

80 85 90 95 00 05


Kvadofjarden

0

10

20

30

40

50

60

70

80

90

100

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=12.9 (7.98,21.0)slope=-11%(-16,-6.1)SD(lr)=23,9.8%,25 yrpower=.29/.10/22%y(07)=3.90 (2.10,7.26)r2=.62, p<.001 *tao=-.53, p<.004 *SD(sm)=36, NS,37%

pia - 09.05.27 13:30, NAP

Phenantrene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

25

30

35

40

80 85 90 95 00 05

n(tot)=16,n(yrs)=14m=6.83 (3.94,11.8)slope=-1.5%(-11,7.6)SD(lr)=51,22%,35 yrpower=.10/.07/41%y(07)= 6.0 ( 2.3,15.7)r2=.01, NStao=-.12, NSSD(sm)=48, NS,38%

Vaderoarna

0

5

10

15

20

25

30

35

40

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=7.71 (5.15,11.6)slope=.28%(-5.8,6.3)SD(lr)=38,14%,30 yrpower=.18/.08/32%y(07)= 7.9 ( 4.0,15.8)r2=.00, NStao=.09, NSSD(sm)=43, NS,36%

Kvadofjarden

0

5

10

15

20

25

30

35

40

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=7.40 (4.87,11.3)slope=-.18%(-7.1,6.8)SD(lr)=41,14%,31 yrpower=.17/.07/33%y(07)= 7.3 ( 3.0,17.4)r2=.00, NStao=-.22, NSSD(sm)=42, NS,34%

pia - 09.05.27 13:33, PA

144

Pyrene, ng/g dry w., blue mussel

Fladen

0

5

10

15

20

25

30

35

40

45

50

80 85 90 95 00 05

n(tot)=16,n(yrs)=14m=8.02 (5.51,11.7)slope=-2.3%(-8.3,3.8)SD(lr)=32,14%,27 yrpower=.17/.09/26%y(07)= 6.6 ( 3.5,12.5)r2=.05, NStao=-.25, NSSD(sm)=32, NS,27%

Vaderoarna

0

5

10

15

20

25

30

35

40

45

50

80 85 90 95 00 05

n(tot)=16,n(yrs)=16m=11.9 (8.39,16.8)slope=-4.6%(-9.1,-.13)SD(lr)=24,9.9%,25 yrpower=.29/.10/23%y(07)= 7.8 ( 4.7,13.1)r2=.26, p<.043 *tao=-.31, p<.094SD(sm)=20, p<.085,19%

Kvadofjarden

0

5

10

15

20

25

30

35

40

45

50

80 84 88 92 96 00 04

n(tot)=16,n(yrs)=16m=6.38 (4.19, 9.7)slope=4.3%(-2.2,11)SD(lr)=41,13%,29 yrpower=.18/.08/31%y(07)=10.1 ( 4.5,23.0)r2=.12, NStao=.17, NSSD(sm)=46, NS,35%

pia - 09.05.27 13:59, PYR

145

25 PFCs, Perfluorinatedcompounds

Updated 09.05.28

Perfluorinated substances have been used industrially and commercially since the beginningof the1950s and it was not until recently (2000) that the main producer, 3M, started to phaseout their production of the main compound of concern, perfluorooctane sulfonate (PFOS)and PFOS-related chemicals (Key et al., 1997 and Holmström et al., 2005).

PFOS has been retrospectively analysed in guillemot eggs from St. Karlsö in a time seriestarting 1968. Additionally, a selection of perfluorinated substances has been analysed inherring liver tissue during the last three years. These comprised perfluorinated carboxylates(PFCAs): perfluorohexanoate (PFHxA), perfluoroheptanoate (PFHpA), perfluorooctanoate(PFOA), perfluorononanoate (PFNA), perfluorodecanoate (PFDcA), perfluoroundecanoate(PFUnA), perfluorododecanoate (PFDoA), perfluorotridecanoate (PFTriA),perfluorotetradecanoate (PFTeA), perfluoropentadecanoate (PFPeDA) as well asperfluorinated sulfonates (PFSs): perfluorobutane sulfonate (PFBS), perfluorohexanesulfonate (PFHxS), perflourooctane sulfonate (PFOS), perfluorodecane sulfonate (PFDcS),perfluorooctane sulfonamide (PFOSA).



A significant increasing trend is observed for PFOS in guillemot eggs with 7-10% per year,which is equal to an increase to 25-30 times higher levels in the early 2000s as compared tothe late 1960ties. Due to change of the analytical method between 2003 and 2004 andrelatively high inter-annual variations, the future trend for PFOS concentrations in theBaltic marine environment cannot be predicted. Further monitoring will reveal if the phaseout by 3M will make a difference for the PFOS concentrations in biota.

146

PFOS, ng/g fresh w., guillemot egg, St Karlso

n(tot)=80,n(yrs)=22

0

200

400

600

800

1000

1200

70 75 80 85 90 95 00 05

m=389 (236 ,640 )slope=8.4%(6.7,10)SD(lr)=7.6,4.6%,21 yrpower=.88/.13/17%y(07)= 1475 ( 1057, 2059)r2=.85, p<.001 *tao=.76, p<.001 *SD(sm)=5.3, p<.008,12%

Data source: ITM, Urs Berger, Katrin Holmstrom 08.03.31 21:14, pfos08

Figure 25.1 Temporal trend of PFOS concentrations in guillemot eggs (ng/g w.w.). The mean annual PFOSvalue shown as red dot in the figure of the time series is based on pooled samples or mean values of individualsamples.



So far only three years (2005-07) of analysis in herring liver are available (pooled samples,12 fish in each) at the old sampling sites and only one year at the new sampling sites.Therefore, the obtained results have to be interpreted carefully. However, it has been shownthat the individual variation of perfluorinated substances is relatively small compared toclassical POPs (Verreault et al., 2007). The spatial variations of 7 perfluorinated substances(three PFSs in Figure 25.2: PFHxS, PFOS and PFOSA and four PFCAs in Figure 25.3:PFNA, PFDcA, PFUnA and PFTriA) are presented below. The selection was based onnumber of results above LOQ.

147

A)

PFHxS

< 1

1 - 2

> 2

ng/g ww

TISS - 09.05.27 15:24, PFHXS

B)

PFOS

< 10

10 - 20

> 20

ng/g ww

TISS - 09.05.27 15:29, PFOS

C)

PFOSA

< 4

4 - 8

> 8

ng/g ww

TISS - 09.05.27 15:32, PFOSA

Figure 25.2 Spatial variation in concentration (w.w.) of A) PFHxS, B) PFOS and C) PFOSA in herring liver.Highest concentration of PFHxS and PFOS were 2.2 ng/g and 25.6 ng/g, respectively. Highest concentrationof PFOSA (9.7 ng/g) was found at Fladen in the Kattegatt.

PFHxS and PFOS show a quite similar spatial pattern, but PFOS concentrations wereapproximately 45 times higher than PFHxS levels. This was as expected, since PFHxS hashardly been produced intentionally, but mainly occurred as by-product in technical PFOS.Furthermore, the distribution of PFOS is quite homogenous along the Swedish coast (withthe exception of Lagnö), which is a result of the extraordinary persistency of the compoundand the long history of use (three decades). Elevated levels may be expected at sites with ahigher population density and associated current emissions from consumer products stillcontaining technical PFOS. PFOSA, however, is not persistent, but a precursor compoundto PFOS. The high concentrations at the west coast reflect a current source probably locatedaround the North Sea. The relatively short environmental half-life of PFOSA does not allowit to diffuse into the Baltic, due to the low water exchange between the two seas.Degradation of PFOSA to PFOS might also contribute to higher PFOS concentrations.Taken into account that liver generally contains about 5 times higher concentrations thanfish muscle, PFOS levels in herring liver are in agreement with levels found in other fishspecies from the Baltic (Swedish Environmental Protection Agency, 2007). PFOSconcentrations in guillemot eggs from 2005, however, are about 200 times higher than in

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herring liver (herring and sprat being the main prey of guillemot), showing the highretention of this compound in guillemot and the transport potential to the forming egg.

A)

PFNA

< 2.5

2.5 - 5

> 5

ng/g ww

TISS - 09.05.27 15:36, PFNA

B)

PFDcA

< 1.5

1.5 - 3

> 3

ng/g ww

TISS - 09.05.27 15:39, PFDcA

C)

PFUnA

< 2

2 - 4

> 4

ng/g ww

TISS - 09.05.27 15:42, PFUnA

D)

PFTriA

< 2

2 - 4

> 4

ng/g ww

TISS - 09.05.27 15:43, PFTriA

Figure 25.3 Spatial variation in PFCA concentrations (w.w.) of A) PFNA, B) PFDcA, C) PFUnA and D)PFTriA in herring liver. Highest concentrations of PFNA (5.64 ng/g) and PFDcA (3.55 ng/g) were found atByxelkrok (in Kalmar sund) in the south Baltic Proper.. Highest concentrations of PFUnA (4.63 ng/g) andPFTriA (5.19 ng/g) were found at Harufjärden in the Bothnian Bay.

PFCAs in the environment can have two types of sources, direct sources (frommanufacturing and use of PFCAs) and indirect sources (from degradation of volatileprecursor compounds) (Prevedouros et al., 2006). PFNA is intentially produced andtherefore probably originates mainly from direct sources (production and use of consumerproducts containing PFNA, such as PTFE products) and waterborne transport to remotelocations. This may partly explain the spatial variations of PFNA in this study, as sewagetreatment plant effluents from industry or larger cities could represent hot-spots. In contrast,PFUnA and PFTriA are unintentionally produced substances, and their presence in theenvironment is probably due to both direct sources (impurities in PFOA and PFNAproductions) and indirect sources (atmospheric transport and degradation of precursors).The fact that the odd-chained PFUnA and PFTriA are higher concentrated than PFDoA andthe homogenous spatial distribution of these compounds supports the theory that indirectsources are important for these long-chain PFCAs. Also levels and compound patterns of

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PFCAs are in good agreement with concentrations in other Baltic fish (SwedishEnvironmental Protection Agency, 2007).

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Comments Concerning the National Swedish Contaminant Monitoring Programme in Marine Biota, 2011

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